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5220 5221 5222 5223 5224 5225 5226 5227 5228 5229 5230 5231 5232 5233 5234 5235 5236 5237 5238 5239 5240 5241 5242 5243 5244 5245 5246 5247 5248 5249 5250 5251 5252 5253 5254 5255 5256 5257 5258 5259 5260 5261 5262 5263 5264 5265 5266 5267 5268 5269 5270 5271 5272 5273 5274 5275 5276 5277 5278 5279 5280 5281 5282 5283 5284 5285 5286 5287 5288 5289 5290 5291 5292 5293 5294 5295 5296 5297 5298 5299 5300 5301 5302 5303 5304 5305 5306 5307 5308 5309 5310 5311 5312 5313 5314 5315 5316 5317 5318 5319 5320 5321 5322 5323 5324 5325 5326 5327 5328 5329 5330 5331 5332 5333 5334 5335 5336 5337 5338 5339 5340 5341 5342 5343 5344 5345 5346 5347 5348 5349 5350 5351 5352 5353 5354 5355 5356 5357 5358 5359 5360 5361 5362 5363 5364 5365 5366 5367 5368 5369 5370 5371 5372 5373 5374 5375 5376 5377 5378 5379 5380 5381 5382 5383 5384 5385 5386 5387 5388 5389 5390 5391 5392 5393 5394 5395 5396 5397 5398 5399 5400 5401 5402 5403 | """Python reimplementation of OpenRA's Normal AI (ModularBot@NormalAI).
Mirrors the C# modular bot architecture with these managers:
- Economy (HarvesterBotModule@normal-turtle)
- Base building (BaseBuilderBotModule@normal)
- Unit production (UnitBuilderBotModule@normal)
- Squads (SquadManagerBotModule@normal)
- Repairs (BuildingRepairBotModule)
- Power (PowerDownBotModule)
All unit weights are taken directly from mods/ra/rules/ai.yaml.
"""
import base64
import random
import struct
from typing import List, Optional, Tuple
from openra_env.models import (
ActionType,
BuildingInfoModel,
CommandModel,
OpenRAAction,
OpenRAObservation,
UnitInfoModel,
)
STANCE_DEFEND = 2
STANCE_ATTACK_ANYTHING = 3
# ---------------------------------------------------------------------------
# Constants from ai.yaml (@normal)
# ---------------------------------------------------------------------------
UNITS_TO_BUILD: dict[str, int] = {
"e1": 65, "e2": 15, "e3": 30, "e4": 15, "e7": 1, "dog": 15,
"shok": 15, "harv": 15, "apc": 30, "jeep": 20, "arty": 15,
"v2rl": 40, "ftrk": 30, "1tnk": 40, "2tnk": 50, "3tnk": 50,
"4tnk": 25, "ttnk": 25, "stnk": 5, "heli": 30, "mh60": 30,
"mig": 30, "yak": 30, "ss": 10, "msub": 10, "dd": 10,
"ca": 10, "pt": 10,
}
UNIT_LIMITS: dict[str, int] = {"dog": 4, "harv": 8, "jeep": 4, "ftrk": 4}
INFANTRY_TYPES = {"e1", "e2", "e3", "e4", "e7", "shok", "dog"}
VEHICLE_TYPES = {"harv", "apc", "jeep", "arty", "v2rl", "ftrk",
"1tnk", "2tnk", "3tnk", "4tnk", "ttnk", "stnk", "mcv"}
AIRCRAFT_TYPES = {"heli", "mh60", "mig", "yak", "hind"}
PLANE_TYPES = {"mig", "yak"}
SHIP_TYPES = {"ss", "msub", "dd", "ca", "pt"}
COMBAT_TYPES = (
{"e1", "e2", "e3", "e4", "e7", "shok"} |
{"apc", "jeep", "arty", "v2rl", "ftrk", "1tnk", "2tnk", "3tnk", "4tnk", "ttnk", "stnk"} |
SHIP_TYPES |
AIRCRAFT_TYPES
)
SQUAD_SIZE = 40
SQUAD_SIZE_RANDOM_BONUS = 30
EXCLUDE_FROM_SQUADS = {"harv", "mcv", "dog", "badr.bomber", "u2"}
BARRACKS_TYPES = {"tent", "barr"}
WAR_FACTORY_TYPES = {"weap"}
PRODUCTION_BUILDING_TYPES = BARRACKS_TYPES | WAR_FACTORY_TYPES
TECH_BUILDING_TYPES = {"dome", "atek", "stek", "fix", "afld", "afld.ukraine", "hpad"}
POWER_DOWN_TYPES = {"dome", "tsla", "mslo", "agun", "sam"}
PROTECTION_TYPES = {
"harv", "mcv", "mslo", "gap", "spen", "syrd", "iron", "pdox", "tsla", "agun",
"dome", "pbox", "hbox", "gun", "ftur", "sam", "atek", "weap", "fact", "proc",
"silo", "hpad", "afld", "afld.ukraine", "powr", "apwr", "stek", "barr", "kenn",
"tent", "fix", "fpwr", "tenf", "syrf", "spef", "weaf", "domf", "fixf", "fapw",
"atef", "pdof", "mslf", "facf",
}
UNIT_QUEUE_ORDER: tuple[tuple[str, set[str]], ...] = (
("Vehicle", VEHICLE_TYPES - {"mcv"}),
("Infantry", INFANTRY_TYPES),
("Plane", PLANE_TYPES),
("Ship", SHIP_TYPES),
("Aircraft", AIRCRAFT_TYPES - PLANE_TYPES),
)
STRUCTURE_QUEUE_TYPES = {"Building", "Defense"}
DEFENSE_STRUCTURE_TYPES = {"pbox", "hbox", "gun", "ftur", "tsla", "agun", "sam", "gap", "mslo"}
ATTACKING_BUILDING_TYPES = {"pbox", "hbox", "gun", "ftur", "tsla", "agun", "sam"}
NAVAL_STRUCTURE_TYPES = {"spen", "syrd"}
ENEMY_FACING_STRUCTURE_TYPES = {"pbox", "hbox", "gun", "ftur", "tsla", "agun", "sam"}
NO_BUILDABLE_AREA_TYPES = NAVAL_STRUCTURE_TYPES | {"silo", "kenn"}
BUILDING_VARIANT_CHOICES: dict[str, tuple[str, ...]] = {
"barracks": ("tent", "barr"),
"afld": ("afld", "afld.ukraine"),
}
BUILDING_CANONICAL_TYPES: dict[str, str] = {"afld.ukraine": "afld"}
BUILDING_DIMENSIONS: dict[str, tuple[int, int]] = {
"fact": (3, 4),
"powr": (2, 3),
"apwr": (3, 3),
"proc": (3, 4),
"weap": (3, 4),
"barr": (2, 3),
"tent": (2, 3),
"dome": (2, 3),
"atek": (2, 3),
"hpad": (2, 3),
"afld": (3, 2),
"afld.ukraine": (3, 2),
"fix": (3, 3),
"stek": (3, 3),
"spen": (3, 3),
"syrd": (3, 3),
"sam": (2, 1),
"mslo": (2, 1),
"silo": (2, 1),
"kenn": (2, 2),
"pbox": (2, 1),
"hbox": (2, 1),
"gun": (2, 2),
"ftur": (2, 2),
"tsla": (2, 2),
"agun": (2, 2),
"gap": (3, 3),
}
BUILDING_TOPLEFT_OFFSETS: dict[str, tuple[int, int]] = {
"fact": (1, 1),
"powr": (1, 1),
"apwr": (1, 1),
"proc": (1, 1),
"weap": (1, 1),
"barr": (1, 1),
"tent": (1, 1),
"dome": (1, 1),
"atek": (1, 1),
"hpad": (1, 1),
"afld": (1, 1),
"afld.ukraine": (1, 1),
"fix": (1, 1),
"stek": (1, 1),
"spen": (1, 1),
"syrd": (1, 1),
"sam": (1, 0),
"mslo": (1, 0),
"silo": (1, 0),
"kenn": (1, 1),
"pbox": (1, 0),
"hbox": (1, 0),
"gun": (1, 1),
"ftur": (1, 1),
"tsla": (1, 1),
"agun": (1, 1),
"gap": (1, 1),
}
BUILDING_COSTS: dict[str, int] = {
"powr": 300, "apwr": 500, "proc": 1400, "weap": 2000,
"barr": 500, "tent": 500, "kenn": 200,
"dome": 1500, "hpad": 500, "afld": 500, "afld.ukraine": 500,
"fix": 1200, "atek": 1500, "stek": 1500, "silo": 150,
"pbox": 600, "hbox": 750, "gun": 800, "ftur": 600,
"tsla": 1200, "agun": 800, "sam": 700,
"gap": 800, "mslo": 2500, "spen": 800, "syrd": 1000,
}
BUILDING_LIMITS: dict[str, int] = {
"barr": 7, "tent": 7, "dome": 1, "weap": 4, "hpad": 4,
"afld": 4, "atek": 1, "stek": 1, "fix": 1, "kenn": 1,
"mslo": 1, "spen": 1, "syrd": 1,
}
BUILDING_FRACTIONS: dict[str, int] = {
"powr": 1, "proc": 1, "tent": 3, "barr": 3, "kenn": 1,
"dome": 1, "weap": 4, "hpad": 1, "spen": 1, "syrd": 1, "afld": 1,
"pbox": 9, "gun": 9, "ftur": 10, "tsla": 5, "gap": 2,
"fix": 1, "agun": 5, "sam": 1, "atek": 1, "stek": 1,
"mslo": 1,
}
BUILDING_DELAYS: dict[str, int] = {
"dome": 6000, "fix": 3000, "pbox": 1500, "gun": 2000,
"ftur": 1500, "tsla": 2800, "kenn": 7000, "atek": 9000,
"stek": 9000, "spen": 6000, "syrd": 6000,
}
UNIT_COMBAT_POWER: dict[str, int] = {
"e1": 25, "e2": 20, "e3": 45, "e4": 35, "e7": 30, "shok": 55,
"dog": 5, "jeep": 45, "apc": 55, "arty": 110, "v2rl": 120,
"ftrk": 70, "1tnk": 90, "2tnk": 120, "3tnk": 145, "4tnk": 135,
"ttnk": 130, "stnk": 120, "heli": 95, "mh60": 90, "mig": 100,
"yak": 95, "hind": 95, "ss": 90, "msub": 90, "dd": 100,
"ca": 120, "pt": 60,
}
BUILDING_THREAT_POWER: dict[str, int] = {
"pbox": 40, "hbox": 45, "gun": 90, "ftur": 110, "tsla": 160,
"agun": 120, "sam": 70, "fact": 55, "weap": 60, "proc": 55,
"dome": 40, "atek": 45, "stek": 45, "fix": 40,
}
TARGET_BUILDING_PRIORITY: dict[str, int] = {
"fact": 100, "weap": 95, "proc": 90, "dome": 82, "fix": 80,
"atek": 78, "stek": 78, "afld": 75, "afld.ukraine": 75, "hpad": 72,
"barr": 68, "tent": 68, "powr": 62, "apwr": 62, "silo": 58,
"tsla": 56, "agun": 54, "ftur": 52, "gun": 50, "sam": 48,
"pbox": 45, "hbox": 42,
}
TARGET_UNIT_PRIORITY: dict[str, int] = {
"mcv": 100, "harv": 95, "v2rl": 90, "arty": 88, "ftrk": 84,
"4tnk": 82, "3tnk": 80, "2tnk": 76, "1tnk": 72, "ttnk": 78,
"stnk": 78, "apc": 65, "jeep": 62, "shok": 58, "e4": 52,
"e3": 50, "e2": 45, "e1": 40, "dog": 10,
}
# Initial build order — same sequence the C# AI follows in practice.
# Uses "barracks" as a placeholder resolved to tent or barr at runtime.
BUILD_ORDER = ["powr", "barracks", "proc", "weap", "powr"]
STRUCTURE_PRODUCTION_ACTIVE_DELAY = 25
STRUCTURE_PRODUCTION_INACTIVE_DELAY = 125
STRUCTURE_PRODUCTION_RANDOM_BONUS_DELAY = 10
STRUCTURE_PRODUCTION_RESUME_DELAY = 1500
PLACEMENT_ATTEMPT_INTERVAL = 25
PLACEMENT_CONFIRMATION_DELAY = 300
MAX_FAILED_PLACEMENT_ATTEMPTS = 8
BASE_BUILD_MIN_RADIUS = 2
BASE_BUILD_MAX_RADIUS = 20
DEFENSE_BUILD_MIN_RADIUS = 5
DEFENSE_BUILD_MAX_RADIUS = 20
CHECK_FOR_WATER_RADIUS = 8
NAVAL_WATER_SCAN_STRIDE = 1
NAVAL_WATER_SCAN_RADIUS = 12
NAVAL_MIN_OPEN_WATER_WINDOWS = 1
NAVAL_MIN_WATER_SCORE = 20
NAVAL_EARLY_BUILD_WATER_SCORE = 22
NAVAL_EARLY_BUILD_CREDIT_BUFFER = 250
NAVAL_BUILD_MAX_RADIUS = 24
NAVAL_GATE_CACHE_TICKS = 151
RESOURCE_MAP_UPDATE_INTERVAL = 151
RESOURCE_PATCH_LINK_RADIUS = 3
RESOURCE_PATCH_MIN_CELLS = 2
RESOURCE_PATCH_SEARCH_MARGIN = 8
RESOURCE_PATCH_THREAT_RADIUS = 12
RESOURCE_PATCH_REFINERY_DISLIKE_RADIUS = 14
MAX_REFINERIES_PER_PATCH = 2
NAVAL_CANDIDATE_MIN_COUNT = 1
RESOURCE_PATCH_MEMORY_MATCH_RADIUS = 6
RESOURCE_PATCH_MAX_CAPACITY = 6
ATTACK_FORCE_INTERVAL = 75
RUSH_INTERVAL = 600
RUSH_TICKS = 4000
ASSIGN_ROLES_INTERVAL = 50
HARVESTER_SCAN_INTERVAL = 50
UNIT_FEEDBACK_TIME = 30
STALE_TARGET_REACHED_RADIUS = 8
STALE_TARGET_REDIRECT_LIMIT = 3
PRODUCTION_MIN_CASH_REQUIREMENT = 500
# C# UnitBuilderBotModule@normal relies on FeedbackTime plus queue occupancy;
# it does not add extra synthetic cooldowns on top of that.
QUEUE_PRODUCTION_DELAYS: dict[str, int] = {}
UNIT_PRODUCTION_DELAYS: dict[str, int] = {}
FOG_CHANNEL = 4 # spatial-map channel: 0=hidden, 0.5=explored, 1=visible
FRONTIER_REFRESH_TICKS = 650
LAST_SEEN_ENEMY_TTL_TICKS = 6000
LAST_SEEN_BASE_TTL_TICKS = 18000
# RA NormalAI does not configure IdleBaseUnitsMaximum for UnitBuilderBotModule@normal,
# so avoid damping production just because squads are currently idling near base.
QUEUE_IDLE_BASE_CAPS: dict[str, int] = {}
IDLE_BASE_UNIT_RADIUS = 15
AIRFIELD_PLANE_CAPACITY = 4
HELIPAD_AIRCRAFT_CAPACITY = 1
INITIAL_HARVESTERS = 4
MINIMUM_EXCESS_POWER = 0
MAXIMUM_EXCESS_POWER = 200
EXCESS_POWER_INCREMENT = 40
EXCESS_POWER_INCREASE_THRESHOLD = 4
INITIAL_MIN_REFINERY_COUNT = 0
ADDITIONAL_MIN_REFINERY_COUNT = 2
NEW_PRODUCTION_CASH_THRESHOLD = 8000
NEW_PRODUCTION_CHANCE = 50
SILO_BUILD_THRESHOLD = 0.8
PROTECT_UNIT_SCAN_RADIUS = 15
PROTECTION_SCAN_RADIUS = 12
PROTECTION_TARGET_BACKOFF_TICKS = 4
HOME_BASE_THREAT_RADIUS = BASE_BUILD_MAX_RADIUS + PROTECTION_SCAN_RADIUS
REPAIR_ALL_BUILDINGS_COOLDOWN = 107
REPAIR_REACTIVE_HP_THRESHOLD = 0.67
POWER_TOGGLE_INTERVAL = 150
ATTACK_SCAN_RADIUS = 12
REGROUP_RADIUS = 14
LOCAL_FIGHT_RADIUS = 12
RUSH_ATTACK_SCAN_RADIUS = 15
RETREAT_HEALTH_THRESHOLD = 0.42
MINIMUM_CONSTRUCTION_YARD_COUNT = 2
ADDITIONAL_CONSTRUCTION_YARD_COUNT = 0
BUILD_ADDITIONAL_MCV_CASH_AMOUNT = 5000
SCAN_FOR_NEW_MCV_INTERVAL = 20
BUILD_MCV_INTERVAL = 101
MCV_MIN_DEPLOY_RADIUS = 2
MCV_MAX_DEPLOY_RADIUS = 20
MCV_TARGET_REACHED_RADIUS = 2
MCV_TRY_MAINTAIN_RANGE = 8
MCV_FRIENDLY_CONYARD_DISLIKE_RANGE = 14
MCV_FRIENDLY_REFINERY_DISLIKE_RANGE = 14
MCV_DEPLOY_OFFSET = (-1, -1)
EXPANSION_TOLERATE_VALUES = (1, 2)
FORCE_EXPANSION_TOLERATE_VALUES = (2, 3)
# Match the C# McvExpansionManager default MoveConyardTick cadence.
CONYARD_UNDEPLOY_COOLDOWN = 5700
MCV_DEPLOY_COMMAND_COOLDOWN = 800
REQUESTED_REFINERY_TTL = 2400
HARVESTER_THREAT_RADIUS = 10
HARVESTER_RETREAT_COOLDOWN = 120
LOW_EFFECT_HARVESTER_SCAN_INTERVAL = 433
RESOURCE_CELLS_PER_HARVESTER = 4
HARVESTER_PATCH_ASSIGN_RADIUS = 12
HARVESTER_REASSIGN_COOLDOWN = 650
HARVESTER_REASSIGN_REFINERY_RADIUS = 14
HARVESTER_LOW_EFFECT_TIMEOUT = 500
HARVESTER_NO_RESOURCE_COOLDOWN = 300
HARVESTER_PROGRESS_MOVE_THRESHOLD = 2
HARVESTER_LOCAL_RESOURCE_MIN = 0.5
BASE_ATTACK_MEMORY_TICKS = 150
BASE_EMERGENCY_VISIBILITY_RADIUS = 5
ATTACK_POINT_MERGE_RADIUS = 4
POST_CONTACT_WINDOW = 2400
RECOVERY_DURATION = 2600
RECOVERY_TRIGGER_PEAK = 24
RECOVERY_DROP_RATIO = 0.6
RECOVERY_MIN_COMBAT = 16
RECOVERY_EXIT_COMBAT = 24
RECOVERY_HARVESTER_CAP = 2
RECOVERY_CLEAR_CONTACT_GAP = 450
RECOVERY_REFINERY_REBUILD_CREDITS = 2000
HOME_GUARD_MIN_RESERVE = 6
HOME_GUARD_MAX_RESERVE = 10
RUSH_SQUAD_MIN_SIZE = 6
AIR_SQUAD_MIN_SIZE = 2
NAVAL_SQUAD_MIN_SIZE = 2
PROTECTION_SQUAD_MIN_SIZE = 4
RESPOND_TO_ATTACK_COOLDOWN = 30
SQUAD_RETREAT_HOLD_TICKS = 180
SQUAD_RECOVER_HOLD_TICKS = 240
RUSH_COMBAT_TYPES = {"e1", "e3", "apc", "jeep", "1tnk", "2tnk", "3tnk", "arty", "v2rl"}
FORCE_COMMIT_UNIT_THRESHOLD = 30
ECONOMY_ATTACK_HOLD_FORCE = 60
TECH_ATTACK_HOLD_FORCE = 70
FORCE_COMMIT_REGROUPS = 3
FORCE_COMMIT_COOLDOWN = 400
FORCE_COMMIT_TIME = 1200 # fallback wave timing (ticks) to mirror NormalAI periodic pushes
FORCE_COMMIT_MIN_SIZE = 12
FORCE_COMMIT_GLOBAL_INTERVAL = 1200 # hard periodic wave, closer to NormalAI cadence
STALE_TARGET_CLEAR_INTERVAL = 2400 # reduce aggressive stale clearing
SEARCH_TARGET_STALL_TICKS = 3600
SQUAD_STUCK_TICKS = 63
NAVAL_FAILURE_DISABLE_TICKS = 12000
MCV_EXPANSION_MODES = ("resource", "base", "current")
MCV_EXPANSION_MODE_FAILURES = 2
FUZZY_ANY_HEALTH = ("NearDead", "Injured", "Normal")
FUZZY_ANY_POWER = ("Weak", "Equal", "Strong")
FUZZY_ANY_SPEED = ("Slow", "Equal", "Fast")
FUZZY_DEFAULT_RULES = (
(("Normal",), FUZZY_ANY_HEALTH, FUZZY_ANY_POWER, FUZZY_ANY_SPEED, "Attack"),
(("Injured",), ("NearDead",), FUZZY_ANY_POWER, FUZZY_ANY_SPEED, "Attack"),
(("Injured",), ("Injured", "Normal"), ("Equal", "Strong"), FUZZY_ANY_SPEED, "Attack"),
(("Injured",), ("Injured", "Normal"), ("Weak",), ("Slow",), "Attack"),
(("Injured",), ("Injured", "Normal"), ("Weak",), ("Equal", "Fast"), "Flee"),
(("Injured",), FUZZY_ANY_HEALTH, FUZZY_ANY_POWER, ("Slow",), "Attack"),
(("NearDead",), ("NearDead", "Injured"), ("Equal", "Strong"), ("Slow", "Equal"), "Attack"),
(("NearDead",), ("NearDead", "Injured"), ("Weak",), ("Equal", "Fast"), "Flee"),
(("NearDead",), ("Normal",), ("Weak",), ("Equal", "Fast"), "Flee"),
(("NearDead",), ("Normal",), ("Equal", "Strong"), ("Fast",), "Flee"),
(("NearDead",), ("Injured",), ("Equal",), ("Fast",), "Flee"),
)
FUZZY_RUSH_RULES = (
(("Normal",), FUZZY_ANY_HEALTH, ("Strong",), FUZZY_ANY_SPEED, "Attack"),
(("Normal",), FUZZY_ANY_HEALTH, ("Weak", "Equal"), FUZZY_ANY_SPEED, "Flee"),
*FUZZY_DEFAULT_RULES[1:],
)
class NormalAIBot:
"""Python reimplementation of OpenRA's Normal AI."""
def __init__(self, verbose: bool = False):
self.verbose = verbose
self.phase = "deploy_mcv"
# Base building
self._build_index = 0
self._placement_count = 0
self._deploy_issued = False
self._last_build_tick: int = -9999
self._next_build_check_tick = 0
self._placement_fail_counts: dict[str, int] = {}
self._placement_pending: dict[str, tuple[str, int, int]] = {}
self._placement_backoff_until: dict[str, int] = {}
self._placement_backoff_snapshot: dict[str, tuple[int, int]] = {}
self._next_placement_attempt_tick: dict[str, int] = {}
self._naval_retry_buildable_count = -1
self._naval_disabled_until = -9999
# Rally
self._rally_set: set[int] = set()
# Squads
self._attack_squad: list[int] = []
self._protection_squad: list[int] = []
self._rush_squad: list[int] = []
self._air_squad: list[int] = []
self._naval_squad: list[int] = []
self._idle_ground_units: list[int] = []
self._temporary_defenders: set[int] = set()
self._last_attack_tick = 0
self._last_attack_eval_tick = -random.randrange(ATTACK_FORCE_INTERVAL) if ATTACK_FORCE_INTERVAL > 0 else 0
rush_jitter = max(1, RUSH_INTERVAL // 20)
self._last_rush_tick = random.randint(-rush_jitter, rush_jitter)
self._last_assign_tick = -random.randrange(ASSIGN_ROLES_INTERVAL) if ASSIGN_ROLES_INTERVAL > 0 else 0
self._protection_backoff = PROTECTION_TARGET_BACKOFF_TICKS
self._protect_from_actor_id = 0
self._protect_from_kind = "point"
self._protect_from_point: Optional[Tuple[int, int]] = None
self._protect_from_until = -9999
self._respond_to_attack_cooldown_until = -9999
self._assault_threshold = self._roll_assault_threshold()
self._squad_states: dict[str, str] = {
"assault": "assemble",
"protection": "assemble",
"rush": "assemble",
"air": "assemble",
"naval": "assemble",
}
self._squad_state_until: dict[str, int] = {}
self._squad_regroup_count: dict[str, int] = {}
self._squad_last_commit_tick: dict[str, int] = {}
self._squad_target_actor_id: dict[str, int] = {}
self._squad_target_kind: dict[str, str] = {}
self._squad_target_point: dict[str, Tuple[int, int]] = {}
self._enemy_base_pos: Optional[Tuple[int, int]] = None
# Bridge only exposes currently visible enemies; keep a short-lived memory.
self._last_seen_enemy_pos: Optional[Tuple[int, int]] = None
self._last_seen_enemy_tick: int = -9999
self._last_seen_base_pos: Optional[Tuple[int, int]] = None
self._last_seen_base_tick: int = -9999
self._rush_target_pos: Optional[Tuple[int, int]] = None
self._rush_target_actor_id = 0
self._rush_target_kind = "point"
self._stale_attack_target: Optional[Tuple[int, int]] = None
self._stale_attack_redirects = 0
self._search_target: Optional[Tuple[int, int]] = None
self._search_target_started_tick = -9999
self._squad_last_progress_tick: dict[str, int] = {}
self._squad_last_progress_pos: dict[str, Tuple[int, int]] = {}
self._squad_last_target_point: dict[str, Tuple[int, int]] = {}
self._squad_leader_id: dict[str, int] = {}
self._attack_commands_issued = 0
self._attack_move_commands_issued = 0
self._unit_target_events = 0
self._building_target_events = 0
self._unique_unit_targets: set[int] = set()
self._unique_building_targets: set[int] = set()
# Repair / power
self._repair_issued: set[int] = set()
self._reactive_repair_targets: set[int] = set()
self._last_repair_tick = -9999
self._powered_down: dict[int, int] = {}
self._last_power_toggle_tick = -9999
# Economy / production
self._last_harvester_scan_tick = -9999
self._last_harvester_reassign_tick = -9999
self._last_unit_tick = -9999
self._current_queue_index = -1
self._unit_requests: list[str] = []
self._queue_delay_until: dict[str, int] = {}
self._unit_delay_until: dict[str, int] = {}
self._last_mcv_scan_tick = random.randrange(SCAN_FOR_NEW_MCV_INTERVAL) if SCAN_FOR_NEW_MCV_INTERVAL > 0 else 0
self._last_mcv_build_tick = random.randrange(BUILD_MCV_INTERVAL) if BUILD_MCV_INTERVAL > 0 else 0
self._last_conyard_undeploy_tick = random.randrange(CONYARD_UNDEPLOY_COOLDOWN) if CONYARD_UNDEPLOY_COOLDOWN > 0 else 0
self._mcv_targets: dict[int, tuple[int, int]] = {}
self._mcv_resource_targets: dict[int, tuple[int, int]] = {}
self._requested_refineries: dict[int, tuple[tuple[int, int], tuple[int, int], int]] = {}
self._mcv_deploy_until: dict[int, int] = {}
self._harvester_retreat_until: dict[int, int] = {}
self._harvester_recent_damage_until: dict[int, int] = {}
self._harvester_reassign_until: dict[int, int] = {}
self._harvester_patch_targets: dict[int, tuple[int, int]] = {}
self._harvester_last_cells: dict[int, tuple[int, int]] = {}
self._harvester_last_progress_tick: dict[int, int] = {}
self._harvester_no_resource_until: dict[int, int] = {}
self._expansion_refinery_goal = 0
self._expansion_refinery_until_tick = -9999
self._combat_peak = 0
self._last_contact_tick = -9999
self._recovery_until_tick = -9999
# Map
self._cached_map_size: Optional[Tuple[int, int]] = None
self._candidate_targets: list[Tuple[int, int]] = []
self._target_index = 0
self._frontier_cache_tick = -9999
self._recent_attack_points: list[tuple[int, int, int]] = []
self._previous_building_hp: dict[int, float] = {}
self._previous_unit_hp: dict[int, float] = {}
self._spatial_raw: bytes = b""
self._spatial_channels = 0
self._last_spatial_update_tick = -9999
self._resource_patches: list[dict[str, float | int]] = []
self._resource_patch_memory: dict[tuple[int, int], dict[str, float | int]] = {}
self._last_naval_gate_tick = -9999
self._cached_naval_gate_ok = False
self._mcv_expansion_mode = MCV_EXPANSION_MODES[0]
self._mcv_expansion_failures = 0
def decide(self, obs: OpenRAObservation) -> OpenRAAction:
commands: List[CommandModel] = []
self._update_map_size(obs)
self._update_spatial_analysis(obs)
self._update_enemy_memory(obs)
self._update_phase(obs)
self._cleanup_dead(obs)
self._update_damage_memory(obs)
self._update_post_contact_state(obs)
commands.extend(self._handle_placement(obs))
if self.phase == "deploy_mcv":
cmd = self._handle_deploy(obs)
if cmd:
commands.append(cmd)
commands.extend(self._handle_rally_points(obs))
commands.extend(self._manage_power(obs))
commands.extend(self._manage_repairs(obs))
commands.extend(self._manage_economy(obs))
commands.extend(self._manage_expansion(obs))
commands.extend(self._manage_base_building(obs))
commands.extend(self._manage_unit_production(obs))
commands.extend(self._manage_squads(obs))
if not commands:
commands.append(CommandModel(action=ActionType.NO_OP))
return OpenRAAction(commands=commands)
def _update_enemy_memory(self, obs: OpenRAObservation) -> None:
"""Update last-seen enemy memory from currently visible enemies/buildings."""
if not (obs.visible_enemies or obs.visible_enemy_buildings):
return
best = self._pick_priority_target(obs, None, None, local_only=False, squad_name="assault")
if best is None:
# Fallback to any visible contact
if obs.visible_enemy_buildings:
b = obs.visible_enemy_buildings[0]
self._last_seen_enemy_pos = (b.cell_x, b.cell_y)
self._last_seen_enemy_tick = obs.tick
self._last_seen_base_pos = (b.cell_x, b.cell_y)
self._last_seen_base_tick = obs.tick
elif obs.visible_enemies:
e = obs.visible_enemies[0]
self._last_seen_enemy_pos = (e.cell_x, e.cell_y)
self._last_seen_enemy_tick = obs.tick
return
_, tx, ty, _, kind = best
self._last_seen_enemy_pos = (tx, ty)
self._last_seen_enemy_tick = obs.tick
if kind == "building":
self._last_seen_base_pos = (tx, ty)
self._last_seen_base_tick = obs.tick
# ── Phase ─────────────────────────────────────────────────────
def _update_phase(self, obs: OpenRAObservation):
has_cy = any(b.type == "fact" for b in obs.buildings)
if self.phase == "deploy_mcv" and has_cy:
self.phase = "build_base"
self._log("Phase -> build_base")
elif self.phase == "build_base":
has_barracks = any(b.type in BARRACKS_TYPES for b in obs.buildings)
if has_barracks:
self.phase = "produce"
self._log("Phase -> produce")
elif self.phase == "produce":
combat = [u for u in obs.units if u.type in COMBAT_TYPES]
if self._build_index >= len(BUILD_ORDER):
self.phase = "active"
self._log(f"Phase -> active ({len(combat)} combat units)")
# ── Deploy MCV ────────────────────────────────────────────────
def _handle_deploy(self, obs: OpenRAObservation) -> Optional[CommandModel]:
if self._deploy_issued:
return None
mcv = next((u for u in obs.units if u.type == "mcv"), None)
if mcv:
self._deploy_issued = True
self._log(f"Deploying MCV #{mcv.actor_id}")
return CommandModel(action=ActionType.DEPLOY, actor_id=mcv.actor_id)
return None
# ── Building placement ────────────────────────────────────────
def _handle_placement(self, obs: OpenRAObservation) -> List[CommandModel]:
commands = []
cy = self._find_building(obs, "fact")
if not cy:
return commands
active_queues: set[str] = set()
counts = self._building_counts(obs)
for prod in obs.production:
if self._is_structure_queue(prod.queue_type) and prod.progress >= 0.99:
queue_type = prod.queue_type
active_queues.add(queue_type)
pending = self._placement_pending.get(queue_type)
current_count = counts.get(self._canonical_building_type(prod.item), 0)
if pending is not None:
pending_item, pending_count, pending_tick = pending
if pending_item == prod.item:
if current_count > pending_count:
self._placement_fail_counts[queue_type] = 0
self._placement_pending.pop(queue_type, None)
continue
if obs.tick < pending_tick + PLACEMENT_CONFIRMATION_DELAY:
continue
self._placement_fail_counts[queue_type] = self._placement_fail_counts.get(queue_type, 0) + 1
self._placement_pending.pop(queue_type, None)
elif pending_item != prod.item:
self._placement_pending.pop(queue_type, None)
self._placement_fail_counts.pop(queue_type, None)
if self._queue_backoff_active(queue_type, obs):
if obs.tick >= self._next_placement_attempt_tick.get(queue_type, -9999):
commands.append(CommandModel(action=ActionType.CANCEL_PRODUCTION, item_type=prod.item))
self._next_placement_attempt_tick[queue_type] = obs.tick + PLACEMENT_ATTEMPT_INTERVAL
continue
if self._placement_fail_counts.get(queue_type, 0) >= MAX_FAILED_PLACEMENT_ATTEMPTS:
commands.append(CommandModel(action=ActionType.CANCEL_PRODUCTION, item_type=prod.item))
if self._canonical_building_type(prod.item) in NAVAL_STRUCTURE_TYPES:
self._naval_retry_buildable_count = self._buildable_area_structure_count(obs)
self._naval_disabled_until = obs.tick + NAVAL_FAILURE_DISABLE_TICKS
self._cached_naval_gate_ok = False
self._last_naval_gate_tick = obs.tick
else:
self._placement_backoff_until[queue_type] = obs.tick + STRUCTURE_PRODUCTION_RESUME_DELAY
self._placement_backoff_snapshot[queue_type] = (
len(obs.buildings),
sum(1 for b in obs.buildings if b.type == "fact"),
)
self._placement_fail_counts[queue_type] = 0
self._placement_pending.pop(queue_type, None)
self._next_placement_attempt_tick[queue_type] = obs.tick + PLACEMENT_ATTEMPT_INTERVAL
self._rewind_build_order_after_cancel(obs, prod.item)
if self._canonical_building_type(prod.item) in NAVAL_STRUCTURE_TYPES:
self._log(f"Canceling {prod.item} after repeated placement failures; disabling naval production")
else:
self._log(f"Canceling {prod.item} after repeated placement failures; backing off {queue_type} queue")
continue
if obs.tick < self._next_placement_attempt_tick.get(queue_type, -9999):
continue
location = self._placement_offset(obs, cy, prod.item)
if location is None:
self._placement_fail_counts[queue_type] = self._placement_fail_counts.get(queue_type, 0) + 1
self._next_placement_attempt_tick[queue_type] = obs.tick + PLACEMENT_ATTEMPT_INTERVAL
continue
x, y = location
commands.append(CommandModel(
action=ActionType.PLACE_BUILDING,
item_type=prod.item,
target_x=x, target_y=y,
))
self._placement_count += 1
self._placement_pending[queue_type] = (prod.item, current_count, obs.tick)
self._next_placement_attempt_tick[queue_type] = obs.tick + PLACEMENT_ATTEMPT_INTERVAL
for queue_type in list(self._placement_pending):
if queue_type not in active_queues:
self._placement_pending.pop(queue_type, None)
self._placement_fail_counts.pop(queue_type, None)
return commands
def _placement_offset(
self,
obs: OpenRAObservation,
cy: BuildingInfoModel,
item_type: str,
) -> Optional[Tuple[int, int]]:
center = self._placement_base_center(obs)
if center is None:
center = self._building_top_left(cy)
center = self._placement_anchor(obs, item_type, center)
cx, cy_y = center
queue_type = self._structure_queue_type(item_type)
retry_index = self._placement_fail_counts.get(queue_type, 0)
min_radius = DEFENSE_BUILD_MIN_RADIUS if item_type in ENEMY_FACING_STRUCTURE_TYPES else BASE_BUILD_MIN_RADIUS
max_radius = DEFENSE_BUILD_MAX_RADIUS if item_type in ENEMY_FACING_STRUCTURE_TYPES else BASE_BUILD_MAX_RADIUS
if item_type not in ENEMY_FACING_STRUCTURE_TYPES:
max_radius += min(retry_index * 4, 20)
candidates = self._placement_candidates(obs, item_type, cx, cy_y, min_radius, max_radius)
if not candidates:
return None
if item_type == "proc":
plan = self._best_refinery_plan(obs)
target = plan["target"] if plan is not None else center
refineries = [b for b in obs.buildings if b.type == "proc"]
candidates.sort(
key=lambda p: (
self._resource_amount_at(*p) > 0.0,
-self._local_resource_score(p[0], p[1], 4),
self._cell_distance(p[0], p[1], target[0], target[1]),
-self._nearest_distance_to_buildings(p[0], p[1], refineries),
self._cell_distance(p[0], p[1], cx, cy_y),
)
)
idx = (self._placement_count + retry_index * 5) % min(len(candidates), 16)
if plan is not None and "request_id" in plan:
self._consume_requested_refinery(plan["request_id"]) # type: ignore[arg-type]
return candidates[idx]
if item_type in NAVAL_STRUCTURE_TYPES:
candidates.sort(
key=lambda p: (
-self._local_water_score(p[0], p[1], 2),
self._cell_distance(p[0], p[1], cx, cy_y),
)
)
idx = (self._placement_count + retry_index * 5) % min(len(candidates), 16)
return candidates[idx]
if item_type in ENEMY_FACING_STRUCTURE_TYPES and self._enemy_base_pos is not None:
tx, ty = self._enemy_base_pos
candidates.sort(key=lambda p: ((p[0] - tx) ** 2 + (p[1] - ty) ** 2, (p[0] - cx) ** 2 + (p[1] - cy_y) ** 2))
idx = (self._placement_count + retry_index * 5) % min(len(candidates), 16)
return candidates[idx]
idx = (self._placement_count + retry_index * 7) % len(candidates)
return candidates[idx]
# ── Rally points ──────────────────────────────────────────────
def _handle_rally_points(self, obs: OpenRAObservation) -> List[CommandModel]:
commands = []
cy = self._find_building(obs, "fact")
if not cy:
return commands
rally_x = cy.cell_x if cy.cell_x > 0 else cy.pos_x // 1024
rally_y = cy.cell_y if cy.cell_y > 0 else cy.pos_y // 1024
for b in obs.buildings:
if b.type in ("tent", "barr", "weap") and b.actor_id not in self._rally_set:
commands.append(CommandModel(
action=ActionType.SET_RALLY_POINT,
actor_id=b.actor_id,
target_x=rally_x, target_y=rally_y,
))
self._rally_set.add(b.actor_id)
return commands
# ── Base Building (fixed order then dynamic) ──────────────────
def _manage_base_building(self, obs: OpenRAObservation) -> List[CommandModel]:
commands = []
if self.phase == "deploy_mcv":
return commands
if obs.tick < self._next_build_check_tick:
return commands
credits = self._available_credits(obs)
if credits < PRODUCTION_MIN_CASH_REQUIREMENT:
self._schedule_next_build_check(obs, active=False)
return commands
# Phase 1: follow the fixed build order
if self._build_index < len(BUILD_ORDER):
item = self._resolve_build_item(obs, BUILD_ORDER[self._build_index])
if item is None:
self._schedule_next_build_check(obs, active=False)
return commands
if not self._structure_queue_available(obs, item):
self._schedule_next_build_check(obs, active=False)
return commands
if self._structure_queue_busy(obs, item):
self._schedule_next_build_check(obs, active=False)
return commands
if self._already_have(obs, item, self._build_index):
self._build_index += 1
return commands
if self._can_produce(obs, item):
cost = self._build_cost(item)
if credits >= cost:
self._log(
f"Building {item} [{self._build_index+1}/{len(BUILD_ORDER)}] "
f"({self._credits_str(obs)})"
)
commands.append(CommandModel(action=ActionType.BUILD, item_type=item))
self._last_build_tick = obs.tick
self._schedule_next_build_check(obs, active=True)
self._build_index += 1
else:
self._schedule_next_build_check(obs, active=False)
else:
self._schedule_next_build_check(obs, active=False)
return commands
# Phase 2: dynamic base building driven by the normal AI priorities.
remaining_credits = credits
picker = self._choose_recovery_building if self._in_recovery_mode(obs) else self._choose_dynamic_building
for queue_type in ("Building", "Defense"):
item = picker(obs, queue_type=queue_type)
if item is None:
continue
if not self._structure_queue_available(obs, item):
continue
if self._structure_queue_busy(obs, item):
continue
if not self._can_produce(obs, item):
continue
cost = self._build_cost(item)
if remaining_credits < cost:
continue
self._log(f"Building {item} (dynamic, {self._credits_str(obs)})")
commands.append(CommandModel(action=ActionType.BUILD, item_type=item))
remaining_credits -= cost
if item == "proc":
self._clear_expansion_refinery_need()
if commands:
self._last_build_tick = obs.tick
self._schedule_next_build_check(obs, active=True)
else:
self._schedule_next_build_check(obs, active=False)
return commands
def _resolve_build_item(self, obs: OpenRAObservation, placeholder: str) -> Optional[str]:
variants = BUILDING_VARIANT_CHOICES.get(placeholder)
if variants is not None:
for btype in variants:
if self._can_produce(obs, btype):
return btype
return None
return placeholder
def _already_have(self, obs: OpenRAObservation, item: str, idx: int) -> bool:
count = sum(1 for b in obs.buildings if b.type == item)
target = sum(1 for i, p in enumerate(BUILD_ORDER[:idx+1])
if self._resolve_build_item(obs, p) == item)
return count >= target
def _choose_dynamic_building(
self,
obs: OpenRAObservation,
queue_type: str = "Building",
) -> Optional[str]:
bldg_counts = self._building_counts(obs)
credits = self._available_credits(obs)
power_balance = obs.economy.power_provided - obs.economy.power_drained
minimum_excess_power = self._minimum_excess_power_target(obs)
power_item = self._best_power_building(obs)
if queue_type == "Defense":
total_buildings = max(1, len(obs.buildings))
candidates = list(BUILDING_FRACTIONS.keys())
random.shuffle(candidates)
for item in candidates:
if BUILDING_DELAYS.get(item, 0) > obs.tick:
continue
resolved_item = self._resolve_build_item(obs, item)
if resolved_item is None or not self._can_produce(obs, resolved_item):
continue
canonical_item = self._canonical_building_type(resolved_item)
if canonical_item not in DEFENSE_STRUCTURE_TYPES:
continue
if not self._structure_queue_available(obs, resolved_item):
continue
count = bldg_counts.get(canonical_item, 0)
limit = BUILDING_LIMITS.get(canonical_item)
if limit is not None and count >= limit:
continue
if count * 100 > BUILDING_FRACTIONS[item] * total_buildings:
continue
return resolved_item
return None
if power_balance < minimum_excess_power and power_item:
return power_item
naval_item = self._preferred_early_naval_building(obs, credits)
if naval_item is not None:
return naval_item
if not self._has_adequate_refinery_count(obs):
if self._can_produce(obs, "proc"):
return "proc"
return power_item
if (
self._expansion_refinery_pending(obs)
and self._can_produce(obs, "proc")
and self._structure_queue_available(obs, "proc")
):
return "proc"
if (
credits > NEW_PRODUCTION_CASH_THRESHOLD
and random.randrange(100) < NEW_PRODUCTION_CHANCE
):
production = self._best_production_building(obs)
if production:
return production
if (
credits > NEW_PRODUCTION_CASH_THRESHOLD
and random.randrange(100) < NEW_PRODUCTION_CHANCE
and self._can_safely_build_naval_structure(obs)
):
naval_production = self._best_naval_production_building(obs)
if naval_production:
return naval_production
if (
obs.economy.resource_capacity > 0
and obs.economy.ore >= obs.economy.resource_capacity * SILO_BUILD_THRESHOLD
and self._can_produce(obs, "silo")
and self._structure_queue_available(obs, "silo")
):
return "silo"
total_buildings = max(1, len(obs.buildings))
candidates = list(BUILDING_FRACTIONS.keys())
random.shuffle(candidates)
for item in candidates:
if BUILDING_DELAYS.get(item, 0) > obs.tick:
continue
resolved_item = self._resolve_build_item(obs, item)
if resolved_item is None or not self._can_produce(obs, resolved_item):
continue
canonical_item = self._canonical_building_type(resolved_item)
if canonical_item in NAVAL_STRUCTURE_TYPES or canonical_item in DEFENSE_STRUCTURE_TYPES:
continue
if not self._structure_queue_available(obs, resolved_item):
continue
count = bldg_counts.get(canonical_item, 0)
limit = BUILDING_LIMITS.get(canonical_item)
if limit is not None and count >= limit:
continue
if count * 100 > BUILDING_FRACTIONS[item] * total_buildings:
continue
return resolved_item
return None
def _choose_recovery_building(
self,
obs: OpenRAObservation,
queue_type: str = "Building",
) -> Optional[str]:
bldg_counts = self._building_counts(obs)
credits = self._available_credits(obs)
power_balance = obs.economy.power_provided - obs.economy.power_drained
minimum_excess_power = self._minimum_excess_power_target(obs)
power_item = self._best_power_building(obs)
if queue_type == "Defense":
if not self._base_under_pressure(obs):
return None
defense_count = sum(bldg_counts.get(item, 0) for item in ("ftur", "gun", "pbox"))
defense_cap = 1 if self._combat_unit_count(obs) < RECOVERY_EXIT_COMBAT else 2
if defense_count >= defense_cap:
return None
for item in ("ftur", "gun", "pbox"):
if not self._can_produce(obs, item):
continue
if not self._structure_queue_available(obs, item):
continue
limit = BUILDING_LIMITS.get(item)
if limit is not None and bldg_counts.get(item, 0) >= limit:
continue
return item
return None
if power_balance < minimum_excess_power and power_item:
return power_item
refinery_count = bldg_counts.get("proc", 0)
if (
refinery_count == 0
and not self._base_under_pressure(obs)
and credits >= RECOVERY_REFINERY_REBUILD_CREDITS
and self._can_produce(obs, "proc")
and self._structure_queue_available(obs, "proc")
):
return "proc"
if not any(b.type in WAR_FACTORY_TYPES for b in obs.buildings):
if self._can_produce(obs, "weap") and self._structure_queue_available(obs, "weap"):
return "weap"
if not any(b.type in BARRACKS_TYPES for b in obs.buildings):
barracks = self._resolve_build_item(obs, "barracks")
if barracks and self._can_produce(obs, barracks) and self._structure_queue_available(obs, barracks):
return barracks
if self._base_under_pressure(obs):
return power_item if power_balance < 0 and power_item else None
return None
# ── Unit Production ───────────────────────────────────────────
def _manage_unit_production(self, obs: OpenRAObservation) -> List[CommandModel]:
commands = []
if self.phase == "deploy_mcv":
return commands
if obs.tick - self._last_unit_tick < UNIT_FEEDBACK_TIME:
return commands
credits = self._available_credits(obs)
if credits < PRODUCTION_MIN_CASH_REQUIREMENT:
return commands
requested = self._queue_requested_unit(obs)
if requested:
self._last_unit_tick = obs.tick
commands.append(requested)
return commands
if not any(self._is_structure_queue(p.queue_type) for p in obs.production):
structure_reservation = self._priority_structure_reservation(obs)
if structure_reservation > 0 and credits < structure_reservation:
return commands
self._last_unit_tick = obs.tick
for _ in range(len(UNIT_QUEUE_ORDER)):
self._current_queue_index = (self._current_queue_index + 1) % len(UNIT_QUEUE_ORDER)
queue_type, allowed = UNIT_QUEUE_ORDER[self._current_queue_index]
if any(p.queue_type == queue_type for p in obs.production):
continue
if self._queue_delay_active(obs, queue_type):
continue
unit = self._pick_unit(obs, allowed)
if unit:
commands.append(CommandModel(action=ActionType.TRAIN, item_type=unit))
self._mark_unit_trained(obs, unit, queue_type)
break
return commands
def _pick_unit(self, obs: OpenRAObservation, allowed: set[str]) -> Optional[str]:
unit_counts: dict[str, int] = {}
total_units = 0
for u in obs.units:
unit_counts[u.type] = unit_counts.get(u.type, 0) + 1
if u.type in UNITS_TO_BUILD:
total_units += 1
for p in obs.production:
unit_counts[p.item] = unit_counts.get(p.item, 0) + 1
if p.item in UNITS_TO_BUILD:
total_units += 1
for item in self._unit_requests:
unit_counts[item] = unit_counts.get(item, 0) + 1
if item in UNITS_TO_BUILD:
total_units += 1
desired: Optional[str] = None
desired_error = float("inf")
candidates = list(allowed)
random.shuffle(candidates)
for utype in candidates:
if utype not in allowed:
continue
if not self._can_produce(obs, utype):
continue
if self._unit_at_limit(obs, utype):
continue
share = self._desired_unit_share(obs, utype, unit_counts)
if share <= 0:
continue
count = unit_counts.get(utype, 0)
error = (count * 100 / total_units - share) if total_units > 0 else -1
if error < 0:
return utype
if error < desired_error:
desired_error = error
desired = utype
return desired
# ── Economy ──────────────────────────────────────────────────
def _manage_economy(self, obs: OpenRAObservation) -> List[CommandModel]:
commands = []
if self.phase == "deploy_mcv":
return commands
if obs.tick - self._last_harvester_scan_tick < HARVESTER_SCAN_INTERVAL:
return commands
self._last_harvester_scan_tick = obs.tick
reassignment_commands, redirected_harvesters = self._reassign_low_effect_harvesters(obs)
commands.extend(reassignment_commands)
patch_states = self._resource_patch_states(obs)
for u in obs.units:
if u.type != "harv":
continue
self._update_harvester_progress(obs, u)
no_resource_target = self._harvester_patch_targets.get(u.actor_id)
if (
no_resource_target is not None
and self._local_resource_score(no_resource_target[0], no_resource_target[1], 2) <= HARVESTER_LOCAL_RESOURCE_MIN
):
self._harvester_no_resource_until[u.actor_id] = obs.tick + HARVESTER_NO_RESOURCE_COOLDOWN
self._harvester_patch_targets.pop(u.actor_id, None)
if u.actor_id in redirected_harvesters:
continue
recent_damage = self._harvester_recently_damaged(obs, u.actor_id)
threat = self._nearest_enemy_to_unit(obs, u, HARVESTER_THREAT_RADIUS)
if threat is not None:
self._last_contact_tick = obs.tick
current_target = self._harvester_patch_targets.get(u.actor_id)
if current_target is not None:
threatened_state = self._nearest_patch_state(
patch_states,
current_target[0],
current_target[1],
HARVESTER_PATCH_ASSIGN_RADIUS,
allow_fallback=True,
)
if threatened_state is not None and int(threatened_state["threat"]) > 0:
self._harvester_patch_targets.pop(u.actor_id, None)
if threat is not None or recent_damage:
fallback = self._pick_harvester_retreat_point(obs, u, patch_states=patch_states)
if fallback is not None and (
threat is not None
or self._cell_distance(u.cell_x, u.cell_y, fallback[0], fallback[1]) > 2
):
commands.append(CommandModel(
action=ActionType.MOVE,
actor_id=u.actor_id,
target_x=fallback[0],
target_y=fallback[1],
))
self._harvester_retreat_until[u.actor_id] = obs.tick + HARVESTER_RETREAT_COOLDOWN
self._harvester_reassign_until[u.actor_id] = obs.tick + HARVESTER_REASSIGN_COOLDOWN
self._harvester_last_progress_tick[u.actor_id] = obs.tick
continue
if self._is_low_effect_harvester(obs, u):
fallback_target = self._fallback_harvest_target(
obs,
u,
patch_states=patch_states,
prefer_safe=recent_damage,
exclude_target=self._harvester_patch_targets.get(u.actor_id),
)
if fallback_target is not None:
commands.append(CommandModel(
action=ActionType.HARVEST,
actor_id=u.actor_id,
target_x=fallback_target[0],
target_y=fallback_target[1],
))
self._harvester_patch_targets[u.actor_id] = fallback_target
self._harvester_reassign_until[u.actor_id] = obs.tick + HARVESTER_REASSIGN_COOLDOWN
self._harvester_last_progress_tick[u.actor_id] = obs.tick
redirected_harvesters.add(u.actor_id)
continue
self._harvester_no_resource_until[u.actor_id] = obs.tick + HARVESTER_NO_RESOURCE_COOLDOWN
if u.is_idle:
target = self._harvester_patch_targets.get(u.actor_id)
target_state = None
if target is not None:
target_state = self._nearest_patch_state(
patch_states,
target[0],
target[1],
HARVESTER_PATCH_ASSIGN_RADIUS,
allow_fallback=True,
)
if (
target is not None
and self._local_resource_score(target[0], target[1], 2) > HARVESTER_LOCAL_RESOURCE_MIN
and (
target_state is None
or (int(target_state["threat"]) == 0 and float(target_state["depletion_ratio"]) < 0.95)
)
):
commands.append(
CommandModel(
action=ActionType.HARVEST,
actor_id=u.actor_id,
target_x=target[0],
target_y=target[1],
)
)
self._harvester_last_progress_tick[u.actor_id] = obs.tick
else:
self._harvester_patch_targets.pop(u.actor_id, None)
target = self._fallback_harvest_target(
obs,
u,
patch_states=patch_states,
prefer_safe=recent_damage or self._base_under_pressure(obs),
)
if target is not None:
commands.append(
CommandModel(
action=ActionType.HARVEST,
actor_id=u.actor_id,
target_x=target[0],
target_y=target[1],
)
)
self._harvester_patch_targets[u.actor_id] = target
self._harvester_last_progress_tick[u.actor_id] = obs.tick
else:
commands.append(CommandModel(action=ActionType.HARVEST, actor_id=u.actor_id))
self._harvester_last_progress_tick[u.actor_id] = obs.tick
self._ensure_harvester_requests(obs)
return commands
# ── Expansion ────────────────────────────────────────────────
def _manage_expansion(self, obs: OpenRAObservation) -> List[CommandModel]:
commands = []
if self.phase == "deploy_mcv" or self._in_recovery_mode(obs):
return commands
if obs.tick - self._last_mcv_build_tick >= BUILD_MCV_INTERVAL:
self._last_mcv_build_tick = obs.tick
self._ensure_mcv_requests(obs)
if obs.tick - self._last_mcv_scan_tick < SCAN_FOR_NEW_MCV_INTERVAL:
return commands
self._last_mcv_scan_tick = obs.tick
undeploy_command = self._maybe_undeploy_conyard_for_expansion(obs)
if undeploy_command is not None:
commands.append(undeploy_command)
conyards = [b for b in obs.buildings if b.type == "fact"]
active_mcvs = [u for u in obs.units if u.type == "mcv"]
if len(conyards) >= MINIMUM_CONSTRUCTION_YARD_COUNT and not active_mcvs:
return commands
for mcv in active_mcvs:
if obs.tick < self._mcv_deploy_until.get(mcv.actor_id, -9999):
continue
target = self._mcv_targets.get(mcv.actor_id)
resource_target = self._mcv_resource_targets.get(mcv.actor_id)
if target is not None and self._cell_distance(mcv.cell_x, mcv.cell_y, *target) <= MCV_TARGET_REACHED_RADIUS:
if self._can_mcv_deploy_at(obs, mcv.cell_x, mcv.cell_y):
self._log(f"Deploying expansion MCV #{mcv.actor_id} at ({mcv.cell_x}, {mcv.cell_y})")
self._remember_requested_refinery(
obs,
mcv.actor_id,
(mcv.cell_x, mcv.cell_y),
resource_target or target,
)
self._remember_expansion_refinery_need(obs)
self._mcv_deploy_until[mcv.actor_id] = obs.tick + MCV_DEPLOY_COMMAND_COOLDOWN
commands.append(CommandModel(action=ActionType.DEPLOY, actor_id=mcv.actor_id))
self._mcv_targets.pop(mcv.actor_id, None)
self._mcv_resource_targets.pop(mcv.actor_id, None)
continue
self._mcv_targets.pop(mcv.actor_id, None)
self._mcv_resource_targets.pop(mcv.actor_id, None)
target = None
if not mcv.is_idle:
continue
if target is None:
expansion_target = self._pick_expansion_target(obs)
if expansion_target is None:
if self._can_mcv_deploy_at(obs, mcv.cell_x, mcv.cell_y):
self._log(f"Deploying expansion MCV #{mcv.actor_id} at ({mcv.cell_x}, {mcv.cell_y})")
self._remember_requested_refinery(
obs,
mcv.actor_id,
(mcv.cell_x, mcv.cell_y),
resource_target or (mcv.cell_x, mcv.cell_y),
)
self._remember_expansion_refinery_need(obs)
self._mcv_deploy_until[mcv.actor_id] = obs.tick + MCV_DEPLOY_COMMAND_COOLDOWN
commands.append(CommandModel(action=ActionType.DEPLOY, actor_id=mcv.actor_id))
self._mcv_resource_targets.pop(mcv.actor_id, None)
continue
target = self._best_mcv_deploy_target(obs, mcv, expansion_target)
if target is None:
if self._can_mcv_deploy_at(obs, mcv.cell_x, mcv.cell_y):
self._log(f"Deploying expansion MCV #{mcv.actor_id} at ({mcv.cell_x}, {mcv.cell_y})")
self._remember_requested_refinery(
obs,
mcv.actor_id,
(mcv.cell_x, mcv.cell_y),
resource_target or expansion_target,
)
self._remember_expansion_refinery_need(obs)
self._mcv_deploy_until[mcv.actor_id] = obs.tick + MCV_DEPLOY_COMMAND_COOLDOWN
commands.append(CommandModel(action=ActionType.DEPLOY, actor_id=mcv.actor_id))
self._mcv_resource_targets.pop(mcv.actor_id, None)
continue
self._mcv_targets[mcv.actor_id] = target
self._mcv_resource_targets[mcv.actor_id] = expansion_target
self._log(f"Dispatching MCV #{mcv.actor_id} -> {target} for expansion {expansion_target}")
if self._cell_distance(mcv.cell_x, mcv.cell_y, *target) <= MCV_TARGET_REACHED_RADIUS:
if self._can_mcv_deploy_at(obs, mcv.cell_x, mcv.cell_y):
self._log(f"Deploying expansion MCV #{mcv.actor_id} at ({mcv.cell_x}, {mcv.cell_y})")
self._remember_requested_refinery(
obs,
mcv.actor_id,
(mcv.cell_x, mcv.cell_y),
resource_target or target,
)
self._remember_expansion_refinery_need(obs)
self._mcv_deploy_until[mcv.actor_id] = obs.tick + MCV_DEPLOY_COMMAND_COOLDOWN
commands.append(CommandModel(action=ActionType.DEPLOY, actor_id=mcv.actor_id))
self._mcv_targets.pop(mcv.actor_id, None)
self._mcv_resource_targets.pop(mcv.actor_id, None)
continue
commands.append(CommandModel(
action=ActionType.MOVE,
actor_id=mcv.actor_id,
target_x=target[0],
target_y=target[1],
))
return commands
def _ensure_harvester_requests(self, obs: OpenRAObservation):
target = self._harvester_target(obs)
current = sum(1 for u in obs.units if u.type == "harv")
current += sum(1 for p in obs.production if p.item == "harv")
current += self._requested_production_count("harv")
if current < target:
self._request_unit_production("harv")
def _hold_attack_for_economy(self, obs: OpenRAObservation) -> bool:
if self._base_under_pressure(obs):
return False
if self._current_requested_refinery(obs) is not None or self._expansion_refinery_pending(obs):
return True
if self._tech_anchor_pending(obs) and self._combat_unit_count(obs) < TECH_ATTACK_HOLD_FORCE:
return True
expanding = bool(self._mcv_targets) or any(u.type == "mcv" for u in obs.units)
expanding = expanding or any(p.item == "mcv" for p in obs.production)
if expanding and self._combat_unit_count(obs) < ECONOMY_ATTACK_HOLD_FORCE:
return True
return False
def _tech_anchor_pending(self, obs: OpenRAObservation) -> bool:
if not self._can_produce(obs, "dome"):
return False
if any(self._canonical_building_type(b.type) == "dome" for b in obs.buildings):
return False
if any(p.item == "dome" for p in obs.production):
return False
return True
def _request_unit_production(self, item_type: str):
if self._requested_production_count(item_type) == 0:
self._unit_requests.append(item_type)
self._log(f"Requesting {item_type} production")
def _requested_production_count(self, item_type: str) -> int:
return sum(1 for item in self._unit_requests if item == item_type)
def _queue_requested_unit(self, obs: OpenRAObservation) -> Optional[CommandModel]:
while self._unit_requests:
item_type = self._unit_requests.pop(0)
if item_type == "harv":
current = self._current_unit_count(obs, "harv")
pending = sum(1 for p in obs.production if p.item == "harv")
queued = self._requested_production_count("harv")
if current + pending + queued >= self._harvester_target(obs):
continue
if self._should_delay_harvester_request(obs, current):
return None
queue_type = self._queue_type_for_unit(item_type)
if queue_type is None:
continue
if item_type not in {"harv", "mcv"} and self._queue_delay_active(obs, queue_type):
return None
if item_type not in {"harv", "mcv"} and self._unit_delay_active(obs, item_type):
return None
if any(p.queue_type == queue_type for p in obs.production):
return None
if not self._can_produce(obs, item_type):
return None
if not self._production_support_available(obs, item_type):
return None
if self._unit_at_limit(obs, item_type):
continue
self._mark_unit_trained(obs, item_type, queue_type)
self._log(f"Training {item_type} (requested)")
return CommandModel(action=ActionType.TRAIN, item_type=item_type)
return None
# ── Squads ────────────────────────────────────────────────────
def _manage_squads(self, obs: OpenRAObservation) -> List[CommandModel]:
commands = []
if self.phase in ("deploy_mcv", "build_base"):
return commands
self._temporary_defenders = set()
if obs.tick - self._last_assign_tick >= ASSIGN_ROLES_INTERVAL:
self._last_assign_tick = obs.tick
self._assign_squad_roles(obs)
commands.extend(self._handle_defense(obs))
if obs.tick - self._last_attack_eval_tick >= ATTACK_FORCE_INTERVAL:
self._last_attack_eval_tick = obs.tick
commands.extend(self._handle_attack(obs))
commands.extend(self._manage_unit_stances(obs))
return commands
def _assign_squad_roles(self, obs: OpenRAObservation):
combat_units = [
u
for u in obs.units
if u.type not in EXCLUDE_FROM_SQUADS and u.type in COMBAT_TYPES
]
air_ids = [u.actor_id for u in combat_units if u.type in AIRCRAFT_TYPES]
naval_ids = [u.actor_id for u in combat_units if u.type in SHIP_TYPES]
ground_units = [u for u in combat_units if u.type not in AIRCRAFT_TYPES | SHIP_TYPES]
ground_by_id = {u.actor_id: u for u in ground_units}
self._air_squad = air_ids
self._naval_squad = naval_ids
# Keep squad membership persistent instead of re-slicing ground units every assign tick.
self._attack_squad = [uid for uid in self._attack_squad if uid in ground_by_id]
self._rush_squad = [uid for uid in self._rush_squad if uid in ground_by_id]
self._idle_ground_units = [
uid for uid in self._idle_ground_units
if uid in ground_by_id and uid not in set(self._attack_squad) and uid not in set(self._rush_squad)
]
self._protection_squad = [
uid for uid in self._protection_squad
if uid in ground_by_id and uid not in set(self._attack_squad) and uid not in set(self._rush_squad)
]
assigned_ground = set(self._attack_squad) | set(self._rush_squad) | set(self._idle_ground_units) | set(self._protection_squad)
unassigned_ground = [u for u in ground_units if u.actor_id not in assigned_ground]
base_center = self._base_center(obs)
if base_center is not None:
unassigned_ground.sort(
key=lambda u: self._cell_distance(u.cell_x, u.cell_y, base_center[0], base_center[1])
)
else:
unassigned_ground.sort(key=lambda u: u.actor_id)
self._idle_ground_units.extend(u.actor_id for u in unassigned_ground)
if self.phase != "active":
return
# OpenRA keeps rush squads separate from assault squads and periodically
# moves all idle base units into the rush squad when the rush trigger fires.
total_ground_troops = len(self._idle_ground_units) + len(self._attack_squad) + len(self._rush_squad) + len(self._protection_squad)
rush_units = [ground_by_id[uid] for uid in self._idle_ground_units if uid in ground_by_id]
hold_for_economy = self._hold_attack_for_economy(obs)
if (
not hold_for_economy
and
not self._base_under_pressure(obs)
and obs.tick - self._last_rush_tick >= RUSH_INTERVAL
and total_ground_troops >= SQUAD_SIZE
and rush_units
):
rush_target = self._select_rush_target(obs, rush_units)
if rush_target is not None:
target_x, target_y, target_actor_id, target_kind = rush_target
launched = list(self._idle_ground_units)
existing_rush = set(self._rush_squad)
self._rush_squad.extend(uid for uid in launched if uid not in existing_rush)
self._idle_ground_units = []
self._last_rush_tick = obs.tick
self._set_squad_target("rush", target_actor_id, target_x, target_y, target_kind)
self._enemy_base_pos = (target_x, target_y)
self._clear_search_target()
self._reset_stale_attack_target()
self._log(f"Launching rush wave ({len(launched)} units) -> {(target_x, target_y)}")
# Launch a fresh assault wave from idle base units once enough have accumulated.
if not self._base_under_pressure(obs):
self._assault_threshold = self._roll_assault_threshold()
if (
not hold_for_economy
and
not self._base_under_pressure(obs)
and len(self._idle_ground_units) >= self._assault_threshold
):
launched = list(self._idle_ground_units)
existing_attack = set(self._attack_squad)
self._attack_squad.extend(uid for uid in launched if uid not in existing_attack)
self._idle_ground_units = []
self._assault_threshold = self._roll_assault_threshold()
self._log(f"Launching assault wave ({len(launched)} units)")
def _squad_units(self, obs: OpenRAObservation, squad_ids: list[int]) -> list[UnitInfoModel]:
alive = {u.actor_id: u for u in obs.units}
return [alive[uid] for uid in squad_ids if uid in alive]
def _set_squad_state(self, squad_name: str, state: str, until: Optional[int] = None):
self._squad_states[squad_name] = state
if until is None:
self._squad_state_until.pop(squad_name, None)
else:
self._squad_state_until[squad_name] = until
def _current_squad_state(self, obs: OpenRAObservation, squad_name: str) -> str:
state = self._squad_states.get(squad_name, "assemble")
hold_until = self._squad_state_until.get(squad_name, -9999)
if state in {"retreat", "recover"} and hold_until > obs.tick:
return state
if state in {"retreat", "recover"} and hold_until <= obs.tick:
self._set_squad_state(squad_name, "assemble")
return "assemble"
return state
def _assemble_squad_commands(
self,
obs: OpenRAObservation,
squad_name: str,
squad_units: list[UnitInfoModel],
) -> List[CommandModel]:
if not squad_units or squad_name == "naval":
return []
anchor = self._base_center(obs)
if anchor is None:
leader = self._select_squad_leader(squad_units)
anchor = (leader.cell_x, leader.cell_y)
commands: list[CommandModel] = []
redirected = 0
for unit in squad_units:
if self._cell_distance(unit.cell_x, unit.cell_y, anchor[0], anchor[1]) <= REGROUP_RADIUS:
continue
commands.append(CommandModel(
action=ActionType.ATTACK_MOVE,
actor_id=unit.actor_id,
target_x=anchor[0],
target_y=anchor[1],
))
redirected += 1
if redirected:
self._log(f"Assembling {squad_name} squad ({redirected}/{len(squad_units)})")
return commands
def _emergency_defense_units(
self,
obs: OpenRAObservation,
needed: int,
threat: Optional[UnitInfoModel] = None,
) -> list[UnitInfoModel]:
if needed <= 0:
return []
alive = {u.actor_id: u for u in obs.units}
reserve_ids = set(self._protection_squad)
candidates = [
alive[uid]
for uid in self._rush_squad + self._attack_squad
if uid in alive
and uid not in reserve_ids
and alive[uid].can_attack
and (
threat is None
or self._cell_distance(alive[uid].cell_x, alive[uid].cell_y, threat.cell_x, threat.cell_y)
<= PROTECT_UNIT_SCAN_RADIUS
)
]
if threat is not None:
base_center = self._base_center(obs) or (threat.cell_x, threat.cell_y)
candidates.sort(
key=lambda u: (
self._cell_distance(u.cell_x, u.cell_y, threat.cell_x, threat.cell_y),
self._cell_distance(u.cell_x, u.cell_y, base_center[0], base_center[1]),
)
)
else:
base_center = self._base_center(obs)
if base_center is not None:
candidates.sort(
key=lambda u: self._cell_distance(u.cell_x, u.cell_y, base_center[0], base_center[1])
)
return candidates[:needed]
def _can_cover_protection_threat(
self,
unit: UnitInfoModel,
threat: UnitInfoModel,
) -> bool:
return self._cell_distance(unit.cell_x, unit.cell_y, threat.cell_x, threat.cell_y) <= PROTECT_UNIT_SCAN_RADIUS
def _manage_unit_stances(self, obs: OpenRAObservation) -> List[CommandModel]:
protection_ids = set(self._protection_squad) | set(self._temporary_defenders)
commands: list[CommandModel] = []
for unit in obs.units:
if unit.type not in COMBAT_TYPES or not unit.can_attack:
continue
desired_stance = STANCE_DEFEND if unit.actor_id in protection_ids else STANCE_ATTACK_ANYTHING
if unit.stance == desired_stance:
continue
commands.append(CommandModel(
action=ActionType.SET_STANCE,
actor_id=unit.actor_id,
target_x=desired_stance,
))
return commands
def _select_ground_squad_leader(
self,
squad_name: str,
squad_units: list[UnitInfoModel],
force_new: bool = False,
) -> UnitInfoModel:
leader_id = self._squad_leader_id.get(squad_name, 0)
if not force_new and leader_id > 0:
for unit in squad_units:
if unit.actor_id == leader_id:
return unit
leader = self._select_squad_leader(squad_units)
self._squad_leader_id[squad_name] = leader.actor_id
return leader
def _unregister_ground_squad(
self,
squad_name: str,
squad_units: list[UnitInfoModel],
) -> None:
unit_ids = [u.actor_id for u in squad_units]
if squad_name == "assault":
self._attack_squad = []
elif squad_name == "rush":
self._rush_squad = []
existing = set(self._idle_ground_units)
self._idle_ground_units.extend(uid for uid in unit_ids if uid not in existing)
self._squad_leader_id.pop(squad_name, None)
self._clear_squad_target(squad_name)
self._set_squad_state(squad_name, "assemble")
def _ground_flee_commands(
self,
obs: OpenRAObservation,
squad_name: str,
squad_units: list[UnitInfoModel],
) -> List[CommandModel]:
fallback = self._random_own_building_cell(obs)
commands: list[CommandModel] = []
if fallback is not None:
tx, ty = fallback
for unit in squad_units:
commands.append(CommandModel(
action=ActionType.MOVE,
actor_id=unit.actor_id,
target_x=tx,
target_y=ty,
))
self._unregister_ground_squad(squad_name, squad_units)
return commands
def _handle_field_squad(
self,
obs: OpenRAObservation,
squad_name: str,
squad_units: list[UnitInfoModel],
minimum_commitment: int,
rush: bool,
) -> List[CommandModel]:
commands: list[CommandModel] = []
if not squad_units:
self._set_squad_state(squad_name, "assemble")
return commands
if squad_name not in self._squad_regroup_count:
self._squad_regroup_count[squad_name] = 0
if squad_name not in self._squad_last_commit_tick:
self._squad_last_commit_tick[squad_name] = -9999
state = self._current_squad_state(obs, squad_name)
literal_ground = squad_name in {"assault", "rush"}
if literal_ground and state in {"retreat", "recover"}:
state = "assemble"
self._set_squad_state(squad_name, "assemble")
leader = (
self._select_ground_squad_leader(squad_name, squad_units)
if literal_ground
else self._select_squad_leader(squad_units)
)
local_enemy_units = self._visible_enemy_units_near(obs, leader.cell_x, leader.cell_y, LOCAL_FIGHT_RADIUS)
local_enemy_buildings = self._visible_enemy_buildings_near(obs, leader.cell_x, leader.cell_y, LOCAL_FIGHT_RADIUS)
if local_enemy_units or local_enemy_buildings:
self._last_contact_tick = obs.tick
self._reset_stale_attack_target()
should_flee = not self._should_take_local_fight(
squad_units,
local_enemy_units,
local_enemy_buildings,
rush=rush or squad_name in {"air", "naval"},
cautious=state == "recover",
squad_name=squad_name,
)
if (
should_flee
and squad_name in {"assault", "rush"}
and state != "assemble"
and self._has_own_building_near(obs, leader.cell_x, leader.cell_y, LOCAL_FIGHT_RADIUS)
):
should_flee = False
if should_flee and literal_ground:
return self._ground_flee_commands(obs, squad_name, squad_units)
if should_flee:
retreat_commands = self._retreat_squad_commands(obs, squad_units, leader)
if retreat_commands:
self._clear_squad_target(squad_name)
self._set_squad_state(squad_name, "retreat", obs.tick + SQUAD_RETREAT_HOLD_TICKS)
self._squad_regroup_count[squad_name] = 0
return retreat_commands
priority_target = self._pick_priority_target(
obs,
leader.cell_x,
leader.cell_y,
local_only=True,
squad_name=squad_name,
)
if priority_target is not None:
self._set_squad_state(squad_name, "commit")
self._set_squad_target(
squad_name,
priority_target[0],
priority_target[1],
priority_target[2],
priority_target[4],
)
if not literal_ground:
focus_commands = self._focus_fire_commands(squad_units, priority_target)
if focus_commands:
return focus_commands
if state == "retreat":
if literal_ground:
return self._ground_flee_commands(obs, squad_name, squad_units)
retreat_commands = self._retreat_squad_commands(obs, squad_units, leader)
if retreat_commands:
return retreat_commands
self._set_squad_state(squad_name, "recover", obs.tick + SQUAD_RECOVER_HOLD_TICKS)
self._squad_regroup_count[squad_name] = 0
if state == "recover" and not (local_enemy_units or local_enemy_buildings):
return self._assemble_squad_commands(obs, squad_name, squad_units)
# Precompute a global force trigger (unconditional periodic wave) to avoid early exit on minimum_commitment
force_global = False
force_commit = False
if squad_name in {"assault", "rush"} and squad_units:
if obs.tick - self._last_attack_tick >= FORCE_COMMIT_GLOBAL_INTERVAL:
force_global = True
force_commit = True
if len(squad_units) < minimum_commitment and not force_global:
self._set_squad_state(squad_name, "assemble")
if squad_name == "assault":
self._assault_threshold = self._roll_assault_threshold()
self._squad_regroup_count[squad_name] = 0
return self._assemble_squad_commands(obs, squad_name, squad_units)
if squad_name == "naval" and not (
local_enemy_units or local_enemy_buildings or obs.visible_enemies or obs.visible_enemy_buildings
):
self._set_squad_state(squad_name, "assemble")
return commands
# Continue evaluating other force-commit paths (regroup/time-based); retain any global trigger from above
if squad_name in {"assault", "rush"}:
regroup_attempts = self._squad_regroup_count.get(squad_name, 0)
last_commit_tick = self._squad_last_commit_tick.get(squad_name, -9999)
time_since_commit = obs.tick - last_commit_tick
if (
regroup_attempts >= FORCE_COMMIT_REGROUPS
and len(squad_units) >= FORCE_COMMIT_UNIT_THRESHOLD
and not local_enemy_units
and not local_enemy_buildings
and time_since_commit >= FORCE_COMMIT_COOLDOWN
and not self._base_under_pressure(obs)
):
force_commit = True
# Timed fallback push toward known target (mirror NormalAI periodic wave)
if (
not force_commit
and len(squad_units) >= max(FORCE_COMMIT_MIN_SIZE, minimum_commitment)
and time_since_commit >= FORCE_COMMIT_TIME
):
force_commit = True
# Hard periodic global wave aligned to NormalAI cadence
if (
not force_commit
# remove size gating to mirror C# periodic pushes
and len(squad_units) >= 1
and obs.tick - self._last_attack_tick >= FORCE_COMMIT_GLOBAL_INTERVAL
):
force_commit = True
force_global = True
regroup_commands = self._regroup_squad_commands(
squad_units,
leader,
regroup_radius=max(1, len(squad_units) // 3) if literal_ground else REGROUP_RADIUS,
min_close_units=len(squad_units) if literal_ground else None,
circular=literal_ground,
)
if regroup_commands and not force_global:
self._set_squad_state(squad_name, "regroup")
self._squad_regroup_count[squad_name] = self._squad_regroup_count.get(squad_name, 0) + 1
return regroup_commands
self._set_squad_state(squad_name, "commit")
target = self._find_attack_target_info(obs, leader.cell_x, leader.cell_y, squad_name=squad_name)
if target is None:
fallback = self._enemy_base_pos or (self._get_map_size()[0] // 2, self._get_map_size()[1] // 2)
tx, ty = fallback
target_actor_id = 0
target_kind = "point"
else:
tx, ty, target_actor_id, target_kind = target
if (
not local_enemy_units
and not local_enemy_buildings
and self._squad_is_stuck(obs, squad_name, leader, (tx, ty))
):
self._log(f"{squad_name.capitalize()} squad stuck near ({tx}, {ty}); clearing target and reevaluating")
self._clear_squad_target(squad_name)
if squad_name == "rush" and self._rush_target_pos == (tx, ty):
self._rush_target_pos = None
self._rush_target_actor_id = 0
self._rush_target_kind = "point"
if self._enemy_base_pos == (tx, ty):
self._enemy_base_pos = None
if target_kind == "search":
self._clear_search_target()
self._reset_stale_attack_target()
tx, ty, target_actor_id, target_kind = self._find_attack_target_info(
obs,
leader.cell_x,
leader.cell_y,
squad_name=squad_name,
)
if squad_name in {"assault", "rush"}:
self._track_stale_attack_target(obs, leader, tx, ty)
if (force_commit or force_global) and squad_name == "assault":
attackers = squad_units
else:
attackers = self._attack_wave_units(obs, squad_units) if squad_name == "assault" else squad_units
direct_attack = self._target_actor_is_visible(obs, target_actor_id, target_kind)
if literal_ground:
direct_attack = False
for unit in attackers:
if direct_attack and (not unit.can_attack or self._busy_attacking(unit)):
continue
commands.append(CommandModel(
action=ActionType.ATTACK if direct_attack else ActionType.ATTACK_MOVE,
actor_id=unit.actor_id,
target_actor_id=target_actor_id if direct_attack else 0,
target_x=tx,
target_y=ty,
))
if commands and not direct_attack:
self._record_attack_issue(
direct_attack=False,
command_count=len(commands),
target_actor_id=target_actor_id,
target_kind=target_kind,
)
if literal_ground:
self._last_attack_tick = obs.tick
self._squad_regroup_count[squad_name] = 0
self._squad_last_commit_tick[squad_name] = obs.tick
elif commands:
self._record_attack_issue(
direct_attack=True,
command_count=len(commands),
target_actor_id=target_actor_id,
target_kind=target_kind,
)
self._log(f"{squad_name.capitalize()} squad: {len(commands)} units attacking {target_kind} at ({tx}, {ty})")
self._last_attack_tick = obs.tick
self._squad_regroup_count[squad_name] = 0
self._squad_last_commit_tick[squad_name] = obs.tick
return commands
def _recruit_protection_units(
self,
obs: OpenRAObservation,
threat: UnitInfoModel,
needed: int,
) -> list[UnitInfoModel]:
if needed <= 0:
return []
alive = {u.actor_id: u for u in obs.units}
candidates = [
alive[uid]
for uid in self._idle_ground_units
if uid in alive
and alive[uid].can_attack
and alive[uid].type not in AIRCRAFT_TYPES | SHIP_TYPES
and self._can_cover_protection_threat(alive[uid], threat)
]
candidates.sort(
key=lambda u: (
self._cell_distance(u.cell_x, u.cell_y, threat.cell_x, threat.cell_y),
self._cell_distance(u.cell_x, u.cell_y, *(self._base_center(obs) or (u.cell_x, u.cell_y))),
)
)
selected = candidates[:needed]
if not selected:
return []
selected_ids = {u.actor_id for u in selected}
existing = set(self._protection_squad)
self._protection_squad.extend(uid for uid in selected_ids if uid not in existing)
self._idle_ground_units = [uid for uid in self._idle_ground_units if uid not in selected_ids]
return selected
def _random_own_building_cell(self, obs: OpenRAObservation) -> Optional[Tuple[int, int]]:
if not obs.buildings:
return self._base_center(obs)
building = random.choice(obs.buildings)
return self._actor_cell(building)
def _release_protection_squad(
self,
obs: OpenRAObservation,
squad_units: list[UnitInfoModel],
reason: str,
) -> List[CommandModel]:
fallback = self._random_own_building_cell(obs)
commands: list[CommandModel] = []
if fallback is not None:
tx, ty = fallback
for unit in squad_units:
commands.append(CommandModel(
action=ActionType.MOVE,
actor_id=unit.actor_id,
target_x=tx,
target_y=ty,
))
if squad_units:
self._log(f"Releasing protection squad ({reason})")
self._protection_squad = []
self._temporary_defenders = set()
self._clear_squad_target("protection")
self._clear_protection_response()
self._set_squad_state("protection", "assemble")
self._protection_backoff = PROTECTION_TARGET_BACKOFF_TICKS
return commands
def _clear_protection_response(self) -> None:
self._protect_from_actor_id = 0
self._protect_from_kind = "point"
self._protect_from_point = None
self._protect_from_until = -9999
def _best_visible_protection_response(
self,
obs: OpenRAObservation,
x: int,
y: int,
) -> Optional[Tuple[int, int, int, str]]:
best: Optional[tuple[tuple[int, int, int], Tuple[int, int, int, str]]] = None
for enemy in self._visible_enemy_units_near(obs, x, y, PROTECT_UNIT_SCAN_RADIUS):
if not enemy.can_attack:
continue
dist = self._cell_distance(x, y, enemy.cell_x, enemy.cell_y)
priority = TARGET_UNIT_PRIORITY.get(enemy.type, 30)
key = (dist, -priority, -int((1.0 - enemy.hp_percent) * 100))
candidate = (enemy.cell_x, enemy.cell_y, enemy.actor_id, "unit")
if best is None or key < best[0]:
best = (key, candidate)
for building in self._visible_enemy_buildings_near(obs, x, y, PROTECT_UNIT_SCAN_RADIUS):
if not self._building_can_attack(building):
continue
bx, by = self._actor_cell(building)
dist = self._cell_distance(x, y, bx, by)
priority = TARGET_BUILDING_PRIORITY.get(building.type, 40)
key = (dist, -priority, -int((1.0 - building.hp_percent) * 100))
candidate = (bx, by, building.actor_id, "building")
if best is None or key < best[0]:
best = (key, candidate)
return best[1] if best is not None else None
def _remember_protection_response(
self,
obs: OpenRAObservation,
x: int,
y: int,
) -> None:
if obs.tick < self._respond_to_attack_cooldown_until:
return
candidate = self._best_visible_protection_response(obs, x, y)
if candidate is None:
return
tx, ty, target_actor_id, target_kind = candidate
self._protect_from_actor_id = target_actor_id
self._protect_from_kind = target_kind
self._protect_from_point = (tx, ty)
self._protect_from_until = obs.tick + 1
self._respond_to_attack_cooldown_until = obs.tick + RESPOND_TO_ATTACK_COOLDOWN
def _current_protection_response(
self,
obs: OpenRAObservation,
) -> Optional[Tuple[int, int, int, str]]:
if obs.tick > self._protect_from_until:
self._clear_protection_response()
return None
if self._protect_from_actor_id > 0:
actor = self._visible_actor_by_target(obs, self._protect_from_actor_id, self._protect_from_kind)
if actor is not None:
tx, ty = self._actor_cell(actor)
self._protect_from_point = (tx, ty)
return tx, ty, self._protect_from_actor_id, self._protect_from_kind
if self._protect_from_point is None:
return None
candidate = self._best_visible_protection_response(obs, self._protect_from_point[0], self._protect_from_point[1])
if candidate is not None:
tx, ty, target_actor_id, target_kind = candidate
self._protect_from_actor_id = target_actor_id
self._protect_from_kind = target_kind
self._protect_from_point = (tx, ty)
return candidate
self._clear_protection_response()
return None
def _retarget_nearby_squads_to_protection(
self,
obs: OpenRAObservation,
tx: int,
ty: int,
target_actor_id: int,
target_kind: str,
) -> None:
for squad_name, squad_ids in (
("assault", self._attack_squad),
("rush", self._rush_squad),
("air", self._air_squad),
("naval", self._naval_squad),
):
squad_units = self._squad_units(obs, squad_ids)
if not squad_units or not any(u.can_attack for u in squad_units):
continue
leader = self._select_squad_leader(squad_units)
if self._cell_distance(leader.cell_x, leader.cell_y, tx, ty) > PROTECT_UNIT_SCAN_RADIUS:
continue
self._set_squad_target(squad_name, target_actor_id, tx, ty, target_kind)
def _find_closest_protection_target(
self,
obs: OpenRAObservation,
leader: UnitInfoModel,
) -> Optional[Tuple[int, int, int, str]]:
best: Optional[Tuple[tuple[int, int, int], Tuple[int, int, int, str]]] = None
for enemy in self._visible_enemy_units_near(obs, leader.cell_x, leader.cell_y, PROTECTION_SCAN_RADIUS):
dist = self._cell_distance(leader.cell_x, leader.cell_y, enemy.cell_x, enemy.cell_y)
priority = TARGET_UNIT_PRIORITY.get(enemy.type, 30 if enemy.can_attack else 10)
key = (dist, -priority, -int((1.0 - enemy.hp_percent) * 100))
candidate = (enemy.cell_x, enemy.cell_y, enemy.actor_id, "unit")
if best is None or key < best[0]:
best = (key, candidate)
for building in self._visible_enemy_buildings_near(obs, leader.cell_x, leader.cell_y, PROTECTION_SCAN_RADIUS):
dist = self._cell_distance(leader.cell_x, leader.cell_y, building.cell_x, building.cell_y)
priority = TARGET_BUILDING_PRIORITY.get(building.type, 40)
key = (dist, -priority, -int((1.0 - building.hp_percent) * 100))
candidate = (building.cell_x, building.cell_y, building.actor_id, "building")
if best is None or key < best[0]:
best = (key, candidate)
return best[1] if best is not None else None
def _pick_protection_threat(
self,
obs: OpenRAObservation,
threat_enemies: list[UnitInfoModel],
) -> Optional[UnitInfoModel]:
if not threat_enemies:
return None
protected_points = self._protected_points(obs)
best: Optional[tuple[tuple[int, int, int, int], UnitInfoModel]] = None
for enemy in threat_enemies:
priority = TARGET_UNIT_PRIORITY.get(enemy.type, 30 if enemy.can_attack else 10)
nearest_protected = min(
(
self._cell_distance(enemy.cell_x, enemy.cell_y, px, py)
for px, py, _ in protected_points
),
default=0,
)
key = (
nearest_protected,
-int(enemy.can_attack),
-priority,
-int((1.0 - enemy.hp_percent) * 100),
)
if best is None or key < best[0]:
best = (key, enemy)
return best[1] if best is not None else None
def _handle_defense(self, obs: OpenRAObservation) -> List[CommandModel]:
response_target = self._current_protection_response(obs)
protection_units = self._squad_units(obs, self._protection_squad)
threat: Optional[UnitInfoModel] = None
if response_target is not None and response_target[3] == "unit":
threat = next((enemy for enemy in obs.visible_enemies if enemy.actor_id == response_target[2]), None)
if threat is not None and response_target is not None:
tx, ty, target_actor_id, target_kind = response_target
self._retarget_nearby_squads_to_protection(obs, tx, ty, target_actor_id, target_kind)
alive_units = {u.actor_id: u for u in obs.units}
idle_defender_count = sum(
1
for uid in self._idle_ground_units
if uid in alive_units
and alive_units[uid].can_attack
and alive_units[uid].type not in AIRCRAFT_TYPES | SHIP_TYPES
and self._can_cover_protection_threat(alive_units[uid], threat)
)
if idle_defender_count > 0:
self._recruit_protection_units(obs, threat, idle_defender_count)
protection_units = self._squad_units(obs, self._protection_squad)
temporary_support: list[UnitInfoModel] = []
self._temporary_defenders = set()
if response_target is None and not protection_units:
self._clear_squad_target("protection")
self._clear_protection_response()
self._set_squad_state("protection", "assemble")
self._protection_backoff = PROTECTION_TARGET_BACKOFF_TICKS
return []
if not protection_units and not temporary_support:
self._clear_squad_target("protection")
self._set_squad_state("protection", "assemble")
return []
leader = self._select_squad_leader(protection_units or temporary_support)
visible_target = self._get_visible_squad_target_info(obs, "protection")
if response_target is not None:
tx, ty, target_actor_id, target_kind = response_target
self._set_squad_target("protection", target_actor_id, tx, ty, target_kind)
self._protection_backoff = PROTECTION_TARGET_BACKOFF_TICKS
elif visible_target is not None:
tx, ty, target_actor_id, target_kind = visible_target
self._protection_backoff = PROTECTION_TARGET_BACKOFF_TICKS
else:
replacement = self._find_closest_protection_target(obs, leader)
if replacement is not None:
tx, ty, target_actor_id, target_kind = replacement
self._set_squad_target("protection", target_actor_id, tx, ty, target_kind)
self._protection_backoff = PROTECTION_TARGET_BACKOFF_TICKS
else:
target_point = self._squad_target_point.get("protection")
if target_point is None:
return self._release_protection_squad(obs, protection_units, "no target")
if self._protection_backoff < 0:
return self._release_protection_squad(obs, protection_units, "lost target")
tx, ty = target_point
target_actor_id = 0
target_kind = "point"
self._protection_backoff -= 1
self._last_contact_tick = obs.tick
self._set_squad_state("protection", "commit")
commands: list[CommandModel] = []
issued_ids: set[int] = set()
direct_attack = target_actor_id > 0 and target_kind in {"unit", "building"}
for defender in protection_units + temporary_support:
if not defender.can_attack or defender.actor_id in issued_ids:
continue
issued_ids.add(defender.actor_id)
commands.append(CommandModel(
action=ActionType.ATTACK if direct_attack else ActionType.ATTACK_MOVE,
actor_id=defender.actor_id,
target_actor_id=target_actor_id if direct_attack else 0,
target_x=tx,
target_y=ty,
))
if commands:
self._record_attack_issue(
direct_attack=direct_attack,
command_count=len(commands),
target_actor_id=target_actor_id,
target_kind=target_kind,
)
return commands
def _handle_attack(self, obs: OpenRAObservation) -> List[CommandModel]:
commands = []
commands.extend(
self._handle_field_squad(
obs,
"assault",
[u for u in self._squad_units(obs, self._attack_squad) if u.actor_id not in self._temporary_defenders],
1,
rush=False,
)
)
commands.extend(
self._handle_field_squad(
obs,
"rush",
[u for u in self._squad_units(obs, self._rush_squad) if u.actor_id not in self._temporary_defenders],
1,
rush=True,
)
)
commands.extend(
self._handle_field_squad(
obs,
"air",
[u for u in self._squad_units(obs, self._air_squad) if u.actor_id not in self._temporary_defenders],
AIR_SQUAD_MIN_SIZE,
rush=False,
)
)
commands.extend(
self._handle_field_squad(
obs,
"naval",
[u for u in self._squad_units(obs, self._naval_squad) if u.actor_id not in self._temporary_defenders],
NAVAL_SQUAD_MIN_SIZE,
rush=False,
)
)
return commands
def _find_attack_target_info(
self,
obs: OpenRAObservation,
leader_x: Optional[int],
leader_y: Optional[int],
squad_name: str = "assault",
) -> Tuple[int, int, int, str]:
current_target = self._get_visible_squad_target_info(obs, squad_name)
if current_target is not None:
tx, ty, target_actor_id, target_kind = current_target
if target_kind == "building":
self._enemy_base_pos = (tx, ty)
elif self._enemy_base_pos is None:
self._enemy_base_pos = (tx, ty)
self._clear_search_target()
self._reset_stale_attack_target()
return current_target
target_point = self._squad_target_point.get(squad_name)
target_actor_id = self._squad_target_actor_id.get(squad_name, 0)
if target_point is not None and target_actor_id > 0:
if not self._should_clear_point_target(obs, target_point, leader_x, leader_y):
return target_point[0], target_point[1], 0, "point"
self._clear_squad_target(squad_name)
if squad_name == "rush" and self._rush_target_pos is not None:
if self._should_clear_point_target(obs, self._rush_target_pos, leader_x, leader_y):
self._log(f"Clearing stale rush target {self._rush_target_pos}")
if self._enemy_base_pos == self._rush_target_pos:
self._enemy_base_pos = None
self._rush_target_pos = None
self._rush_target_actor_id = 0
self._rush_target_kind = "point"
self._reset_stale_attack_target()
else:
self._enemy_base_pos = self._rush_target_pos
self._clear_search_target()
return (
self._rush_target_pos[0],
self._rush_target_pos[1],
self._rush_target_actor_id,
self._rush_target_kind,
)
closest = self._pick_closest_visible_target(obs, leader_x, leader_y, squad_name=squad_name)
if closest is not None:
actor_id, tx, ty, _, kind = closest
self._set_squad_target(squad_name, actor_id, tx, ty, kind)
if kind == "building":
self._enemy_base_pos = (tx, ty)
elif self._enemy_base_pos is None:
self._enemy_base_pos = (tx, ty)
self._clear_search_target()
self._reset_stale_attack_target()
return tx, ty, actor_id, kind
if self._enemy_base_pos and self._should_clear_enemy_base_target(obs, leader_x, leader_y):
self._log(f"Clearing stale enemy base target {self._enemy_base_pos}")
if self._rush_target_pos == self._enemy_base_pos:
self._rush_target_pos = None
self._rush_target_actor_id = 0
self._rush_target_kind = "point"
self._enemy_base_pos = None
self._reset_stale_attack_target()
if self._enemy_base_pos:
self._clear_search_target()
self._set_squad_target(squad_name, 0, self._enemy_base_pos[0], self._enemy_base_pos[1], "point")
return self._enemy_base_pos[0], self._enemy_base_pos[1], 0, "point"
# If we don't have a persistent base target, prefer last-seen memory before blind exploration.
if self._last_seen_base_pos is not None and obs.tick - self._last_seen_base_tick <= LAST_SEEN_BASE_TTL_TICKS:
self._clear_search_target()
self._set_squad_target(squad_name, 0, self._last_seen_base_pos[0], self._last_seen_base_pos[1], "point")
return self._last_seen_base_pos[0], self._last_seen_base_pos[1], 0, "point"
if self._last_seen_enemy_pos is not None and obs.tick - self._last_seen_enemy_tick <= LAST_SEEN_ENEMY_TTL_TICKS:
self._clear_search_target()
self._set_squad_target(squad_name, 0, self._last_seen_enemy_pos[0], self._last_seen_enemy_pos[1], "point")
return self._last_seen_enemy_pos[0], self._last_seen_enemy_pos[1], 0, "point"
tx, ty = self._select_search_target(obs, leader_x, leader_y)
self._set_squad_target(squad_name, 0, tx, ty, "search")
return tx, ty, 0, "search"
def _find_attack_target(
self,
obs: OpenRAObservation,
leader_x: Optional[int],
leader_y: Optional[int],
squad_name: str = "assault",
) -> Tuple[int, int]:
tx, ty, _, _ = self._find_attack_target_info(obs, leader_x, leader_y, squad_name=squad_name)
return tx, ty
def _track_stale_attack_target(
self,
obs: OpenRAObservation,
leader: UnitInfoModel,
tx: int,
ty: int,
) -> None:
if obs.visible_enemies or obs.visible_enemy_buildings:
self._reset_stale_attack_target()
return
target = (tx, ty)
reached_target = self._cell_distance(leader.cell_x, leader.cell_y, tx, ty) <= STALE_TARGET_REACHED_RADIUS
if self._stale_attack_target == target:
if reached_target:
self._stale_attack_redirects += 1
else:
self._stale_attack_target = target
self._stale_attack_redirects = 1 if reached_target else 0
def _should_clear_enemy_base_target(
self,
obs: OpenRAObservation,
leader_x: Optional[int],
leader_y: Optional[int],
) -> bool:
return self._enemy_base_pos is not None and self._should_clear_point_target(
obs,
self._enemy_base_pos,
leader_x,
leader_y,
)
def _should_clear_point_target(
self,
obs: OpenRAObservation,
target: Tuple[int, int],
leader_x: Optional[int],
leader_y: Optional[int],
) -> bool:
if obs.visible_enemies or obs.visible_enemy_buildings:
return False
recent_enemy_sighting_tick = max(self._last_seen_enemy_tick, self._last_seen_base_tick)
if obs.tick - recent_enemy_sighting_tick < STALE_TARGET_CLEAR_INTERVAL:
return False
tx, ty = target
if (
leader_x is not None
and leader_y is not None
and self._cell_distance(leader_x, leader_y, tx, ty) <= STALE_TARGET_REACHED_RADIUS
):
# Only clear after we have actually explored the area around the point.
# Otherwise we can drop targets prematurely and re-sweep the same zones.
if self._spatial_raw:
return self._area_is_explored(tx, ty, radius=5, threshold=0.5)
return True
return (
self._stale_attack_target == target
and self._stale_attack_redirects >= STALE_TARGET_REDIRECT_LIMIT
)
def _squad_is_stuck(
self,
obs: OpenRAObservation,
squad_name: str,
leader: UnitInfoModel,
target: Tuple[int, int],
) -> bool:
current_pos = (leader.cell_x, leader.cell_y)
previous_pos = self._squad_last_progress_pos.get(squad_name)
previous_target = self._squad_last_target_point.get(squad_name)
if previous_pos != current_pos or previous_target != target:
self._squad_last_progress_pos[squad_name] = current_pos
self._squad_last_target_point[squad_name] = target
self._squad_last_progress_tick[squad_name] = obs.tick
return False
last_tick = self._squad_last_progress_tick.get(squad_name, obs.tick)
if obs.tick <= last_tick + SQUAD_STUCK_TICKS:
return False
self._squad_last_progress_tick[squad_name] = obs.tick
return True
def _reset_stale_attack_target(self) -> None:
self._stale_attack_target = None
self._stale_attack_redirects = 0
def _clear_search_target(self) -> None:
self._search_target = None
self._search_target_started_tick = -9999
def _set_squad_target(
self,
squad_name: str,
target_actor_id: int,
tx: int,
ty: int,
target_kind: str,
) -> None:
self._squad_target_point[squad_name] = (tx, ty)
if target_actor_id > 0 and target_kind in {"unit", "building"}:
self._squad_target_actor_id[squad_name] = target_actor_id
self._squad_target_kind[squad_name] = target_kind
else:
self._squad_target_actor_id.pop(squad_name, None)
self._squad_target_kind.pop(squad_name, None)
if squad_name == "rush":
self._rush_target_pos = (tx, ty)
self._rush_target_actor_id = target_actor_id if target_kind in {"unit", "building"} else 0
self._rush_target_kind = target_kind
def _clear_squad_target(self, squad_name: str) -> None:
self._squad_target_actor_id.pop(squad_name, None)
self._squad_target_kind.pop(squad_name, None)
self._squad_target_point.pop(squad_name, None)
if squad_name == "rush":
self._rush_target_pos = None
self._rush_target_actor_id = 0
self._rush_target_kind = "point"
def _visible_actor_by_target(
self,
obs: OpenRAObservation,
target_actor_id: int,
target_kind: str,
):
if target_actor_id <= 0:
return None
if target_kind == "unit":
return next((enemy for enemy in obs.visible_enemies if enemy.actor_id == target_actor_id), None)
if target_kind == "building":
return next((building for building in obs.visible_enemy_buildings if building.actor_id == target_actor_id), None)
return None
def _get_visible_squad_target_info(
self,
obs: OpenRAObservation,
squad_name: str,
) -> Optional[Tuple[int, int, int, str]]:
target_actor_id = self._squad_target_actor_id.get(squad_name, 0)
target_kind = self._squad_target_kind.get(squad_name, "point")
actor = self._visible_actor_by_target(obs, target_actor_id, target_kind)
if actor is None:
return None
tx, ty = self._actor_cell(actor)
self._squad_target_point[squad_name] = (tx, ty)
return tx, ty, target_actor_id, target_kind
def _advance_search_target(self, obs: OpenRAObservation) -> Tuple[int, int]:
if not self._candidate_targets:
self._candidate_targets = self._search_grid(obs)
self._target_index = 0
target = self._candidate_targets[self._target_index % len(self._candidate_targets)]
self._target_index = (self._target_index + 1) % len(self._candidate_targets)
self._search_target = target
self._search_target_started_tick = obs.tick
self._log(f"Search target -> {target}")
return target
def _select_search_target(
self,
obs: OpenRAObservation,
leader_x: Optional[int],
leader_y: Optional[int],
) -> Tuple[int, int]:
if self._search_target is None:
return self._advance_search_target(obs)
if (
leader_x is not None
and leader_y is not None
and self._cell_distance(leader_x, leader_y, self._search_target[0], self._search_target[1])
<= STALE_TARGET_REACHED_RADIUS
):
return self._advance_search_target(obs)
if obs.tick - self._search_target_started_tick >= SEARCH_TARGET_STALL_TICKS:
self._log(f"Search target stalled -> rotating from {self._search_target}")
return self._advance_search_target(obs)
return self._search_target
def _spatial_fog(self, x: int, y: int) -> float:
return self._spatial_value(x, y, FOG_CHANNEL, 0.0)
def _area_is_explored(self, x: int, y: int, radius: int = 5, threshold: float = 0.5) -> bool:
"""True if any cell near (x,y) is explored/visible (fog>=0.5)."""
if not self._spatial_raw:
return False
w, h = self._get_map_size()
x0 = max(0, x - radius)
y0 = max(0, y - radius)
x1 = min(w - 1, x + radius)
y1 = min(h - 1, y + radius)
for yy in range(y0, y1 + 1):
for xx in range(x0, x1 + 1):
if self._spatial_fog(xx, yy) >= threshold:
return True
return False
def _search_grid(self, obs: OpenRAObservation) -> list[Tuple[int, int]]:
"""Exploration candidates.
Prefer frontier/unexplored regions when spatial fog exists (channel 4).
Otherwise fall back to a coarse far-from-base grid.
"""
w, h = self._get_map_size()
cy = self._find_building(obs, "fact")
if not cy:
return [(w // 2, h // 2)]
bx = cy.cell_x if cy.cell_x > 0 else cy.pos_x // 1024
by = cy.cell_y if cy.cell_y > 0 else cy.pos_y // 1024
if self._spatial_raw and obs.tick - self._frontier_cache_tick >= FRONTIER_REFRESH_TICKS:
self._frontier_cache_tick = obs.tick
block = 8
gx_max = max(1, w // block)
gy_max = max(1, h // block)
scored: list[tuple[float, tuple[int, int]]] = []
for gx in range(gx_max):
for gy in range(gy_max):
cx = min(w - 1, gx * block + block // 2)
cyy = min(h - 1, gy * block + block // 2)
if not self._is_passable_cell(cx, cyy):
continue
unseen = 0
frontier = 0
samples = 0
for sx in (0, block // 2, block - 1):
for sy in (0, block // 2, block - 1):
x = gx * block + sx
y = gy * block + sy
if x < 0 or y < 0 or x >= w or y >= h:
continue
samples += 1
fog = self._spatial_fog(x, y)
if fog < 0.25:
unseen += 1
# frontier if adjacent to explored/visible
for dx, dy in ((1, 0), (-1, 0), (0, 1), (0, -1)):
nx, ny = x + dx, y + dy
if 0 <= nx < w and 0 <= ny < h and self._spatial_fog(nx, ny) >= 0.5:
frontier += 1
break
if samples <= 0:
continue
unseen_frac = unseen / samples
frontier_frac = frontier / samples
d2 = (cx - bx) * (cx - bx) + (cyy - by) * (cyy - by)
score = unseen_frac * 3.0 + frontier_frac * 4.0 + (d2 ** 0.5) * 0.01
if d2 < 20 * 20:
score -= 1.5
scored.append((score, (cx, cyy)))
scored.sort(key=lambda t: t[0], reverse=True)
candidates = [p for _, p in scored[:40]]
if candidates:
return candidates
n = 3
cw, ch = max(1, w // n), max(1, h // n)
centers = [(cw * gx + cw // 2, ch * gy + ch // 2)
for gx in range(n) for gy in range(n)]
min_d2 = (min(w, h) // n) ** 2
far = [p for p in centers if (p[0] - bx) ** 2 + (p[1] - by) ** 2 > min_d2]
if not far:
far = [(w // 2, h // 2)]
far.sort(key=lambda p: (p[0] - bx) ** 2 + (p[1] - by) ** 2, reverse=True)
return far
# ── Repairs ───────────────────────────────────────────────────
def _manage_repairs(self, obs: OpenRAObservation) -> List[CommandModel]:
commands = []
for b in obs.buildings:
if b.hp_percent >= 0.98:
self._repair_issued.discard(b.actor_id)
self._reactive_repair_targets.discard(b.actor_id)
continue
if (
b.actor_id in self._reactive_repair_targets
and not b.is_repairing
and b.actor_id not in self._repair_issued
and self._available_credits(obs) >= 500
):
commands.append(CommandModel(action=ActionType.REPAIR, actor_id=b.actor_id))
self._repair_issued.add(b.actor_id)
self._reactive_repair_targets.discard(b.actor_id)
if obs.tick - self._last_repair_tick < REPAIR_ALL_BUILDINGS_COOLDOWN:
return commands
self._last_repair_tick = obs.tick
for b in obs.buildings:
if (b.hp_percent < 0.75 and not b.is_repairing
and b.actor_id not in self._repair_issued
and self._available_credits(obs) >= 500):
commands.append(CommandModel(action=ActionType.REPAIR, actor_id=b.actor_id))
self._repair_issued.add(b.actor_id)
return commands
# ── Power ─────────────────────────────────────────────────────
def _manage_power(self, obs: OpenRAObservation) -> List[CommandModel]:
commands = []
if obs.tick - self._last_power_toggle_tick < POWER_TOGGLE_INTERVAL:
return commands
self._last_power_toggle_tick = obs.tick
bal = obs.economy.power_provided - obs.economy.power_drained
buildings_by_id = {b.actor_id: b for b in obs.buildings}
self._powered_down = {
actor_id: expected_change
for actor_id, expected_change in self._powered_down.items()
if actor_id in buildings_by_id and not buildings_by_id[actor_id].is_powered
}
if bal > 0 and self._powered_down:
for actor_id, expected_change in sorted(
self._powered_down.items(),
key=lambda item: item[1],
reverse=True,
):
if bal - expected_change < 0:
continue
commands.append(CommandModel(action=ActionType.POWER_DOWN, actor_id=actor_id))
bal -= expected_change
for cmd in commands:
self._powered_down.pop(cmd.actor_id, None)
return commands
if bal < 0:
candidates: list[tuple[int, int]] = []
for b in obs.buildings:
if b.type not in POWER_DOWN_TYPES or not b.is_powered or b.actor_id in self._powered_down:
continue
expected_change = max(0, -b.power_amount)
if expected_change <= 0:
continue
candidates.append((expected_change, b.actor_id))
for expected_change, actor_id in sorted(candidates):
commands.append(CommandModel(action=ActionType.POWER_DOWN, actor_id=actor_id))
self._powered_down[actor_id] = expected_change
bal += expected_change
if bal >= 0:
break
return commands
# ── Cleanup ───────────────────────────────────────────────────
def _cleanup_dead(self, obs: OpenRAObservation):
alive = {u.actor_id for u in obs.units}
self._attack_squad = [uid for uid in self._attack_squad if uid in alive]
self._protection_squad = [uid for uid in self._protection_squad if uid in alive]
self._rush_squad = [uid for uid in self._rush_squad if uid in alive]
self._air_squad = [uid for uid in self._air_squad if uid in alive]
self._naval_squad = [uid for uid in self._naval_squad if uid in alive]
self._idle_ground_units = [uid for uid in self._idle_ground_units if uid in alive]
self._temporary_defenders &= alive
self._squad_regroup_count = {k: v for k, v in self._squad_regroup_count.items() if k in self._squad_states}
self._squad_last_progress_tick = {
squad_name: tick
for squad_name, tick in self._squad_last_progress_tick.items()
if squad_name in self._squad_states
}
self._squad_last_progress_pos = {
squad_name: pos
for squad_name, pos in self._squad_last_progress_pos.items()
if squad_name in self._squad_states
}
self._squad_last_target_point = {
squad_name: target
for squad_name, target in self._squad_last_target_point.items()
if squad_name in self._squad_states
}
self._squad_leader_id = {
squad_name: actor_id
for squad_name, actor_id in self._squad_leader_id.items()
if squad_name in self._squad_states and actor_id in alive
}
self._squad_target_actor_id = {
squad_name: actor_id
for squad_name, actor_id in self._squad_target_actor_id.items()
if squad_name in self._squad_states
}
self._squad_target_kind = {
squad_name: kind
for squad_name, kind in self._squad_target_kind.items()
if squad_name in self._squad_states
}
self._squad_target_point = {
squad_name: point
for squad_name, point in self._squad_target_point.items()
if squad_name in self._squad_states
}
self._previous_unit_hp = {
actor_id: hp
for actor_id, hp in self._previous_unit_hp.items()
if actor_id in alive
}
self._mcv_targets = {
actor_id: target
for actor_id, target in self._mcv_targets.items()
if actor_id in alive
}
self._mcv_resource_targets = {
actor_id: target
for actor_id, target in self._mcv_resource_targets.items()
if actor_id in alive
}
alive_b = {b.actor_id for b in obs.buildings}
self._requested_refineries = {
actor_id: request
for actor_id, request in self._requested_refineries.items()
if request[2] > obs.tick
}
self._mcv_deploy_until = {
actor_id: tick
for actor_id, tick in self._mcv_deploy_until.items()
if actor_id in alive or actor_id in alive_b
if tick > obs.tick
}
self._repair_issued &= alive_b
self._reactive_repair_targets &= alive_b
self._rally_set &= alive_b
self._previous_building_hp = {
actor_id: hp
for actor_id, hp in self._previous_building_hp.items()
if actor_id in alive_b
}
self._powered_down = {
actor_id: expected_change
for actor_id, expected_change in self._powered_down.items()
if actor_id in alive_b
}
self._harvester_retreat_until = {
actor_id: tick
for actor_id, tick in self._harvester_retreat_until.items()
if actor_id in alive
}
self._harvester_recent_damage_until = {
actor_id: tick
for actor_id, tick in self._harvester_recent_damage_until.items()
if actor_id in alive
}
self._harvester_reassign_until = {
actor_id: tick
for actor_id, tick in self._harvester_reassign_until.items()
if actor_id in alive
}
self._harvester_patch_targets = {
actor_id: target
for actor_id, target in self._harvester_patch_targets.items()
if actor_id in alive
}
self._harvester_last_cells = {
actor_id: cell
for actor_id, cell in self._harvester_last_cells.items()
if actor_id in alive
}
self._harvester_last_progress_tick = {
actor_id: tick
for actor_id, tick in self._harvester_last_progress_tick.items()
if actor_id in alive
}
self._harvester_no_resource_until = {
actor_id: tick
for actor_id, tick in self._harvester_no_resource_until.items()
if actor_id in alive
}
self._recent_attack_points = [
(x, y, tick)
for x, y, tick in self._recent_attack_points
if obs.tick - tick <= BASE_ATTACK_MEMORY_TICKS
]
if not self._rush_squad:
self._clear_squad_target("rush")
if not self._attack_squad:
self._clear_squad_target("assault")
def _update_damage_memory(self, obs: OpenRAObservation):
self._recent_attack_points = [
(x, y, tick)
for x, y, tick in self._recent_attack_points
if obs.tick - tick <= BASE_ATTACK_MEMORY_TICKS
]
next_building_hp: dict[int, float] = {}
for building in obs.buildings:
next_building_hp[building.actor_id] = building.hp_percent
previous_hp = self._previous_building_hp.get(building.actor_id)
if previous_hp is not None and building.hp_percent + 1e-6 < previous_hp:
bx, by = self._actor_cell(building)
if self._is_home_base_cell(obs, bx, by):
self._remember_attack_point(bx, by, obs.tick)
if building.type in PROTECTION_TYPES:
self._remember_protection_response(obs, bx, by)
if previous_hp >= REPAIR_REACTIVE_HP_THRESHOLD and building.hp_percent < REPAIR_REACTIVE_HP_THRESHOLD:
self._reactive_repair_targets.add(building.actor_id)
self._previous_building_hp = next_building_hp
next_unit_hp: dict[int, float] = {}
for unit in obs.units:
next_unit_hp[unit.actor_id] = unit.hp_percent
previous_hp = self._previous_unit_hp.get(unit.actor_id)
if previous_hp is not None and unit.hp_percent + 1e-6 < previous_hp:
if unit.type == "mcv" or (
unit.type == "harv" and self._is_local_protection_asset(obs, unit.cell_x, unit.cell_y)
):
self._remember_attack_point(unit.cell_x, unit.cell_y, obs.tick)
self._remember_protection_response(obs, unit.cell_x, unit.cell_y)
if unit.type == "harv":
self._harvester_recent_damage_until[unit.actor_id] = obs.tick + HARVESTER_RETREAT_COOLDOWN
self._previous_unit_hp = next_unit_hp
def _remember_attack_point(self, x: int, y: int, tick: int) -> None:
for idx, (px, py, _) in enumerate(self._recent_attack_points):
if self._cell_distance(x, y, px, py) <= ATTACK_POINT_MERGE_RADIUS:
self._recent_attack_points[idx] = ((px + x) // 2, (py + y) // 2, tick)
return
self._recent_attack_points.append((x, y, tick))
def _update_post_contact_state(self, obs: OpenRAObservation):
combat_count = self._combat_unit_count(obs)
was_recovering = self._in_recovery_mode(obs)
self._combat_peak = max(self._combat_peak, combat_count)
if self._base_under_pressure(obs):
self._last_contact_tick = obs.tick
had_recent_contact = obs.tick - self._last_contact_tick <= POST_CONTACT_WINDOW
collapse_threshold = max(RECOVERY_MIN_COMBAT, int(self._combat_peak * RECOVERY_DROP_RATIO))
if had_recent_contact and self._combat_peak >= RECOVERY_TRIGGER_PEAK and combat_count <= collapse_threshold:
self._recovery_until_tick = max(self._recovery_until_tick, obs.tick + RECOVERY_DURATION)
if (
was_recovering
and combat_count >= max(RECOVERY_EXIT_COMBAT, int(self._combat_peak * 0.75))
and obs.tick - self._last_contact_tick >= RECOVERY_CLEAR_CONTACT_GAP
and not self._base_under_pressure(obs)
):
self._recovery_until_tick = obs.tick
self._combat_peak = combat_count
elif not had_recent_contact and combat_count < RECOVERY_TRIGGER_PEAK:
self._combat_peak = max(combat_count, self._combat_peak - 1)
is_recovering = self._in_recovery_mode(obs)
if not was_recovering and is_recovering:
self._log(f"Recovery mode -> rebuild ({combat_count} combat units, peak {self._combat_peak})")
elif was_recovering and not is_recovering:
self._log(f"Recovery mode -> cleared ({combat_count} combat units)")
# ── Map ───────────────────────────────────────────────────────
def _update_map_size(self, obs: OpenRAObservation):
w, h = obs.map_info.width, obs.map_info.height
if w > 0 and h > 0:
if self._cached_map_size is None:
self._cached_map_size = (w, h)
else:
cw, ch = self._cached_map_size
if w < cw or h < ch:
self._cached_map_size = (w, h)
self._candidate_targets = []
self._target_index = 0
self._clear_search_target()
def _get_map_size(self) -> Tuple[int, int]:
return self._cached_map_size or (128, 128)
def _update_spatial_analysis(self, obs: OpenRAObservation):
if not obs.spatial_map or obs.spatial_channels <= 0:
return
if (
self._spatial_raw
and obs.tick >= self._last_spatial_update_tick
and obs.tick - self._last_spatial_update_tick < RESOURCE_MAP_UPDATE_INTERVAL
):
return
try:
raw = base64.b64decode(obs.spatial_map)
except Exception:
return
w, h = self._get_map_size()
channels = obs.spatial_channels
if w <= 0 or h <= 0 or channels <= 0:
return
self._spatial_raw = raw
self._spatial_channels = channels
self._last_spatial_update_tick = obs.tick
resource_cells: list[tuple[int, int, float]] = []
for y in range(h):
for x in range(w):
base_idx = (y * w + x) * channels
try:
resource = struct.unpack_from("f", raw, (base_idx + 2) * 4)[0]
except struct.error:
continue
if resource > 0:
resource_cells.append((x, y, resource))
self._resource_patches = self._cluster_resource_patches(resource_cells)
self._sync_resource_patch_memory(obs.tick)
def _cluster_resource_patches(
self,
resource_cells: list[tuple[int, int, float]],
) -> list[dict[str, float | int]]:
if not resource_cells:
return []
density_by_cell = {(x, y): density for x, y, density in resource_cells}
unvisited = set(density_by_cell.keys())
patches: list[dict[str, float | int]] = []
while unvisited:
start = unvisited.pop()
queue = [start]
cluster = [(start[0], start[1], density_by_cell[start])]
while queue:
cx, cy = queue.pop()
for dx in range(-RESOURCE_PATCH_LINK_RADIUS, RESOURCE_PATCH_LINK_RADIUS + 1):
for dy in range(-RESOURCE_PATCH_LINK_RADIUS, RESOURCE_PATCH_LINK_RADIUS + 1):
nx, ny = cx + dx, cy + dy
if (nx, ny) not in unvisited:
continue
unvisited.remove((nx, ny))
queue.append((nx, ny))
cluster.append((nx, ny, density_by_cell[(nx, ny)]))
if len(cluster) < RESOURCE_PATCH_MIN_CELLS:
continue
center_x = sum(c[0] for c in cluster) // len(cluster)
center_y = sum(c[1] for c in cluster) // len(cluster)
total_density = sum(c[2] for c in cluster)
resource_center = min(
cluster,
key=lambda c: ((c[0] - center_x) ** 2 + (c[1] - center_y) ** 2, -c[2]),
)
patches.append(
{
"center_x": center_x,
"center_y": center_y,
"resource_center_x": resource_center[0],
"resource_center_y": resource_center[1],
"cells": len(cluster),
"total_density": round(total_density, 1),
}
)
patches.sort(key=lambda p: (int(p["cells"]), float(p["total_density"])), reverse=True)
return patches
def _sync_resource_patch_memory(self, tick: int):
previous = dict(self._resource_patch_memory)
refreshed: dict[tuple[int, int], dict[str, float | int]] = {}
for patch in self._resource_patches:
target = self._patch_target(patch)
match_key: Optional[tuple[int, int]] = None
best_dist = RESOURCE_PATCH_MEMORY_MATCH_RADIUS + 1
for key in previous:
dist = self._cell_distance(target[0], target[1], key[0], key[1])
if dist <= RESOURCE_PATCH_MEMORY_MATCH_RADIUS and dist < best_dist:
match_key = key
best_dist = dist
memory = previous.pop(match_key) if match_key is not None else {}
current_density = float(patch["total_density"])
previous_density = float(memory.get("last_density", current_density))
peak_density = max(
current_density,
previous_density,
float(memory.get("peak_density", current_density)),
)
density_drop_ratio = 0.0
if previous_density > 1e-6 and current_density < previous_density:
density_drop_ratio = (previous_density - current_density) / previous_density
depletion_ratio = 0.0
if peak_density > 1e-6 and current_density < peak_density:
depletion_ratio = (peak_density - current_density) / peak_density
depletion_trend = float(memory.get("depletion_trend", 0.0)) * 0.7 + density_drop_ratio * 0.3
refreshed[target] = {
"last_density": current_density,
"peak_density": peak_density,
"depletion_ratio": max(0.0, min(1.0, depletion_ratio)),
"depletion_trend": max(0.0, min(1.0, depletion_trend)),
"last_tick": tick,
}
self._resource_patch_memory = refreshed
def _patch_memory(self, patch: dict[str, float | int]) -> dict[str, float | int]:
return self._resource_patch_memory.get(self._patch_target(patch), {})
def _nearest_anchor_distance(
self,
x: int,
y: int,
anchors: list[tuple[int, int]],
) -> int:
if not anchors:
return 0
return min(self._cell_distance(x, y, ax, ay) for ax, ay in anchors)
def _resource_patch_capacity(
self,
total_density: float,
cells: int,
refinery_count: int,
depletion_ratio: float,
threat: int,
) -> int:
capacity = max(1, cells // RESOURCE_CELLS_PER_HARVESTER)
if total_density >= cells * 2.0:
capacity += 1
if total_density >= cells * 3.5:
capacity += 1
if refinery_count > 0:
capacity += 1
capacity = min(RESOURCE_PATCH_MAX_CAPACITY, capacity)
floor = 1 if refinery_count > 0 else 0
if depletion_ratio >= 0.55:
capacity = max(floor, capacity - 1)
if threat > 0:
capacity = max(0, capacity - min(threat, 2))
return capacity
def _spatial_value(self, x: int, y: int, channel: int, default: float = 0.0) -> float:
w, h = self._get_map_size()
if (
not self._spatial_raw
or self._spatial_channels <= channel
or x < 0
or y < 0
or x >= w
or y >= h
):
return default
base_idx = (y * w + x) * self._spatial_channels
try:
return struct.unpack_from("f", self._spatial_raw, (base_idx + channel) * 4)[0]
except struct.error:
return default
def _resource_amount_at(self, x: int, y: int) -> float:
return self._spatial_value(x, y, 2, 0.0)
def _terrain_index_at(self, x: int, y: int) -> int:
return int(self._spatial_value(x, y, 0, 0.0))
def _is_passable_cell(self, x: int, y: int) -> bool:
if not self._spatial_raw:
return True
return self._spatial_value(x, y, 3, 1.0) > 0.5
def _is_water_candidate_cell(self, x: int, y: int) -> bool:
if not self._spatial_raw:
return False
# Prefer terrain-index water (common case), but fall back to a human-visible cue:
# large contiguous impassable regions (water) in the passability channel.
if self._terrain_index_at(x, y) in {7, 8}:
return True
passability = self._spatial_value(x, y, 3, 1.0)
if passability > 0.05:
return False
# Reject isolated impassables (cliffs/rocks) by requiring most neighbors
# to also be strongly impassable.
imp = 0
for dx in (-1, 0, 1):
for dy in (-1, 0, 1):
if self._spatial_value(x + dx, y + dy, 3, 1.0) <= 0.05:
imp += 1
return imp >= 8
def _is_open_water_cell(self, x: int, y: int) -> bool:
w, h = self._get_map_size()
if x <= 0 or y <= 0 or x >= w - 1 or y >= h - 1:
return False
for dx in (-1, 0, 1):
for dy in (-1, 0, 1):
if not self._is_water_candidate_cell(x + dx, y + dy):
return False
return True
def _local_resource_score(self, x: int, y: int, radius: int) -> float:
total = 0.0
for dx in range(-radius, radius + 1):
for dy in range(-radius, radius + 1):
total += self._resource_amount_at(x + dx, y + dy)
return total
def _local_water_score(self, x: int, y: int, radius: int) -> int:
total = 0
for dx in range(-radius, radius + 1):
for dy in range(-radius, radius + 1):
if self._is_water_candidate_cell(x + dx, y + dy):
total += 1
return total
# ── Helpers ───────────────────────────────────────────────────
def _find_building(self, obs: OpenRAObservation, btype: str) -> Optional[BuildingInfoModel]:
return next((b for b in obs.buildings if b.type == btype), None)
def _is_structure_queue(self, queue_type: str) -> bool:
return queue_type in STRUCTURE_QUEUE_TYPES
def _structure_queue_busy(self, obs: OpenRAObservation, item_type: str) -> bool:
queue_type = self._structure_queue_type(item_type)
return any(p.queue_type == queue_type for p in obs.production)
def _available_credits(self, obs: OpenRAObservation) -> int:
# OpenRA splits spendable funds between liquid cash and stored ore/resources.
return obs.economy.cash + obs.economy.ore
def _combat_unit_count(self, obs: OpenRAObservation) -> int:
return sum(1 for u in obs.units if u.type in COMBAT_TYPES)
def _in_recovery_mode(self, obs: OpenRAObservation) -> bool:
return obs.tick < self._recovery_until_tick
def _base_center(self, obs: OpenRAObservation) -> Optional[Tuple[int, int]]:
cy = self._find_building(obs, "fact")
if cy is not None:
return (
cy.cell_x if cy.cell_x > 0 else cy.pos_x // 1024,
cy.cell_y if cy.cell_y > 0 else cy.pos_y // 1024,
)
if obs.buildings:
b = obs.buildings[0]
return (
b.cell_x if b.cell_x > 0 else b.pos_x // 1024,
b.cell_y if b.cell_y > 0 else b.pos_y // 1024,
)
return None
def _is_home_base_cell(self, obs: OpenRAObservation, x: int, y: int) -> bool:
base_center = self._base_center(obs)
return base_center is None or self._cell_distance(x, y, base_center[0], base_center[1]) <= HOME_BASE_THREAT_RADIUS
def _is_local_protection_asset(self, obs: OpenRAObservation, x: int, y: int) -> bool:
if self._is_home_base_cell(obs, x, y):
return True
anchors = [
b
for b in obs.buildings
if self._canonical_building_type(b.type) in {"fact", "proc"}
and self._is_home_base_cell(
obs,
b.cell_x if b.cell_x > 0 else b.pos_x // 1024,
b.cell_y if b.cell_y > 0 else b.pos_y // 1024,
)
]
if anchors and self._nearest_distance_to_buildings(x, y, anchors) <= PROTECT_UNIT_SCAN_RADIUS:
return True
return False
def _placement_base_center(self, obs: OpenRAObservation) -> Optional[Tuple[int, int]]:
cy = self._find_building(obs, "fact")
if cy is not None:
return self._building_top_left(cy)
if obs.buildings:
return self._building_top_left(obs.buildings[0])
return None
def _protected_points(self, obs: OpenRAObservation) -> list[tuple[int, int, int]]:
protected_points: list[tuple[int, int, int]] = []
for b in obs.buildings:
if b.type in PROTECTION_TYPES:
bx = b.cell_x if b.cell_x > 0 else b.pos_x // 1024
by = b.cell_y if b.cell_y > 0 else b.pos_y // 1024
if not self._is_home_base_cell(obs, bx, by):
continue
protected_points.append((bx, by, PROTECTION_SCAN_RADIUS))
for u in obs.units:
if u.type in {"harv", "mcv"} and self._is_local_protection_asset(obs, u.cell_x, u.cell_y):
protected_points.append((u.cell_x, u.cell_y, PROTECT_UNIT_SCAN_RADIUS))
return protected_points
def _base_threat_enemies(self, obs: OpenRAObservation) -> list[UnitInfoModel]:
protected_points = self._protected_points(obs)
emergency_points = [
(x, y, BASE_EMERGENCY_VISIBILITY_RADIUS)
for x, y, tick in self._recent_attack_points
if obs.tick - tick <= BASE_ATTACK_MEMORY_TICKS
]
threat_points = protected_points + emergency_points
if not threat_points:
return []
return [
e for e in obs.visible_enemies
if any(self._cell_distance(e.cell_x, e.cell_y, px, py) <= radius for px, py, radius in threat_points)
]
def _base_under_pressure(self, obs: OpenRAObservation) -> bool:
return bool(self._base_threat_enemies(obs))
def _nearest_enemy_to_unit(
self,
obs: OpenRAObservation,
unit: UnitInfoModel,
radius: int,
) -> Optional[UnitInfoModel]:
nearby = self._visible_enemy_units_near(obs, unit.cell_x, unit.cell_y, radius)
if not nearby:
return None
return min(nearby, key=lambda e: self._cell_distance(unit.cell_x, unit.cell_y, e.cell_x, e.cell_y))
def _pick_harvester_retreat_point(
self,
obs: OpenRAObservation,
harvester: UnitInfoModel,
patch_states: Optional[list[dict[str, object]]] = None,
) -> Optional[Tuple[int, int]]:
refineries = [b for b in obs.buildings if b.type == "proc"]
if patch_states is None:
patch_states = self._resource_patch_states(obs)
threatened_patch = self._nearest_patch_state(
patch_states,
harvester.cell_x,
harvester.cell_y,
HARVESTER_PATCH_ASSIGN_RADIUS,
allow_fallback=True,
)
avoid_target: Optional[tuple[int, int]] = None
if threatened_patch is not None and int(threatened_patch["threat"]) > 0:
avoid_target = threatened_patch["target"] # type: ignore[index]
if refineries:
scored_refineries = sorted(
refineries,
key=lambda b: (
1
if avoid_target is not None and self._cell_distance(
b.cell_x if b.cell_x > 0 else b.pos_x // 1024,
b.cell_y if b.cell_y > 0 else b.pos_y // 1024,
avoid_target[0],
avoid_target[1],
) <= HARVESTER_PATCH_ASSIGN_RADIUS
else 0,
self._cell_distance(
harvester.cell_x,
harvester.cell_y,
b.cell_x if b.cell_x > 0 else b.pos_x // 1024,
b.cell_y if b.cell_y > 0 else b.pos_y // 1024,
),
),
)
best = scored_refineries[0]
return (
best.cell_x if best.cell_x > 0 else best.pos_x // 1024,
best.cell_y if best.cell_y > 0 else best.pos_y // 1024,
)
return self._base_center(obs)
def _harvester_recently_damaged(self, obs: OpenRAObservation, actor_id: int) -> bool:
return obs.tick < self._harvester_recent_damage_until.get(actor_id, -9999)
def _update_harvester_progress(self, obs: OpenRAObservation, harvester: UnitInfoModel):
actor_id = harvester.actor_id
current_cell = (harvester.cell_x, harvester.cell_y)
previous_cell = self._harvester_last_cells.get(actor_id)
patch_target = self._harvester_patch_targets.get(actor_id)
if previous_cell is None:
self._harvester_last_progress_tick[actor_id] = obs.tick
else:
moved = self._cell_distance(current_cell[0], current_cell[1], previous_cell[0], previous_cell[1])
if moved >= HARVESTER_PROGRESS_MOVE_THRESHOLD:
self._harvester_last_progress_tick[actor_id] = obs.tick
if patch_target is not None and self._cell_distance(current_cell[0], current_cell[1], patch_target[0], patch_target[1]) <= 2:
self._harvester_last_progress_tick[actor_id] = obs.tick
self._harvester_last_cells[actor_id] = current_cell
def _is_low_effect_harvester(self, obs: OpenRAObservation, harvester: UnitInfoModel) -> bool:
if harvester.is_idle:
return False
if obs.tick < self._harvester_retreat_until.get(harvester.actor_id, -9999):
return False
if self._harvester_recently_damaged(obs, harvester.actor_id):
return False
if obs.tick < self._harvester_no_resource_until.get(harvester.actor_id, -9999):
return False
last_progress = self._harvester_last_progress_tick.get(harvester.actor_id, obs.tick)
if obs.tick - last_progress < HARVESTER_LOW_EFFECT_TIMEOUT:
return False
patch_target = self._harvester_patch_targets.get(harvester.actor_id)
if patch_target is not None and self._local_resource_score(patch_target[0], patch_target[1], 2) <= HARVESTER_LOCAL_RESOURCE_MIN:
return True
activity = harvester.current_activity.lower()
if "harvest" in activity or "move" in activity or "dock" in activity:
return True
return False
def _fallback_harvest_target(
self,
obs: OpenRAObservation,
harvester: UnitInfoModel,
patch_states: Optional[list[dict[str, object]]] = None,
prefer_safe: bool = False,
exclude_target: Optional[tuple[int, int]] = None,
) -> Optional[tuple[int, int]]:
if patch_states is None:
patch_states = self._resource_patch_states(obs)
scan_origin = self._pick_harvester_retreat_point(obs, harvester, patch_states=patch_states)
if scan_origin is None:
scan_origin = (harvester.cell_x, harvester.cell_y)
current_target = self._harvester_patch_targets.get(harvester.actor_id)
candidates = []
for state in patch_states:
target = state["target"] # type: ignore[index]
if exclude_target is not None and target == exclude_target:
continue
if int(state["capacity"]) <= 0:
continue
if float(state["depletion_ratio"]) >= 0.95:
continue
if self._local_resource_score(target[0], target[1], 2) <= HARVESTER_LOCAL_RESOURCE_MIN:
continue
if prefer_safe and int(state["threat"]) > 0:
continue
candidates.append(state)
if not candidates:
return None
best = max(
candidates,
key=lambda state: (
int(state["score"])
+ (140 if int(state["refinery_count"]) > 0 else 0)
+ (80 if current_target == state["target"] and int(state["threat"]) == 0 and not prefer_safe else 0)
- int(max(0.0, float(state["saturation"]) - 1.0) * 420)
- self._cell_distance(
scan_origin[0],
scan_origin[1],
state["target"][0], # type: ignore[index]
state["target"][1], # type: ignore[index]
) * 18
-self._cell_distance(
harvester.cell_x,
harvester.cell_y,
state["target"][0], # type: ignore[index]
state["target"][1], # type: ignore[index]
) * 6
- int(state["threat"]) * (480 if prefer_safe else 260),
),
)
return best["target"] # type: ignore[return-value]
def _pending_build_cost(self, obs: OpenRAObservation) -> int:
if self._build_index >= len(BUILD_ORDER):
return 0
item = self._resolve_build_item(obs, BUILD_ORDER[self._build_index])
if item is None or self._already_have(obs, item, self._build_index):
return 0
if not self._can_produce(obs, item):
return 0
if not self._structure_queue_available(obs, item):
return 0
return self._build_cost(item)
def _building_counts(self, obs: OpenRAObservation) -> dict[str, int]:
counts: dict[str, int] = {}
for b in obs.buildings:
btype = self._canonical_building_type(b.type)
counts[btype] = counts.get(btype, 0) + 1
return counts
def _canonical_building_type(self, item_type: str) -> str:
return BUILDING_CANONICAL_TYPES.get(item_type, item_type)
def _build_cost(self, item_type: str) -> int:
canonical = self._canonical_building_type(item_type)
return BUILDING_COSTS.get(item_type, BUILDING_COSTS.get(canonical, 500))
def _building_dimensions(self, item_type: str) -> tuple[int, int]:
canonical = self._canonical_building_type(item_type)
return BUILDING_DIMENSIONS.get(item_type, BUILDING_DIMENSIONS.get(canonical, (2, 2)))
def _building_top_left(self, building: BuildingInfoModel) -> tuple[int, int]:
canonical = self._canonical_building_type(building.type)
offset_x, offset_y = BUILDING_TOPLEFT_OFFSETS.get(
building.type,
BUILDING_TOPLEFT_OFFSETS.get(canonical, (0, 0)),
)
return (
(building.cell_x if building.cell_x > 0 else building.pos_x // 1024) - offset_x,
(building.cell_y if building.cell_y > 0 else building.pos_y // 1024) - offset_y,
)
def _occupied_building_cells(self, obs: OpenRAObservation) -> set[tuple[int, int]]:
occupied: set[tuple[int, int]] = set()
for building in obs.buildings:
bx, by = self._building_top_left(building)
width, height = self._building_dimensions(building.type)
for dx in range(width):
for dy in range(height):
occupied.add((bx + dx, by + dy))
return occupied
def _buildable_area_cells(self, obs: OpenRAObservation) -> set[tuple[int, int]]:
cells: set[tuple[int, int]] = set()
for building in obs.buildings:
if self._canonical_building_type(building.type) in NO_BUILDABLE_AREA_TYPES:
continue
bx, by = self._building_top_left(building)
width, height = self._building_dimensions(building.type)
for dx in range(width):
for dy in range(height):
cells.add((bx + dx, by + dy))
return cells
def _buildable_area_structure_count(self, obs: OpenRAObservation) -> int:
return sum(
1
for building in obs.buildings
if self._canonical_building_type(building.type) not in NO_BUILDABLE_AREA_TYPES
)
def _footprint_close_enough_to_base(
self,
top_left_x: int,
top_left_y: int,
width: int,
height: int,
base_cells: set[tuple[int, int]],
radius: int,
) -> bool:
if not base_cells:
return False
max_x = top_left_x + width - 1
max_y = top_left_y + height - 1
for bx, by in base_cells:
dx = 0 if top_left_x <= bx <= max_x else min(abs(bx - top_left_x), abs(bx - max_x))
dy = 0 if top_left_y <= by <= max_y else min(abs(by - top_left_y), abs(by - max_y))
if max(dx, dy) <= radius:
return True
return False
def _candidate_fits_building_footprint(
self,
obs: OpenRAObservation,
item_type: str,
top_left_x: int,
top_left_y: int,
occupied: Optional[set[tuple[int, int]]] = None,
base_cells: Optional[set[tuple[int, int]]] = None,
) -> bool:
width, height = self._building_dimensions(item_type)
w, h = self._get_map_size()
if top_left_x < 0 or top_left_y < 0 or top_left_x + width > w or top_left_y + height > h:
return False
occupied = occupied or self._occupied_building_cells(obs)
is_naval = self._canonical_building_type(item_type) in NAVAL_STRUCTURE_TYPES
if base_cells is None:
base_cells = self._buildable_area_cells(obs)
if is_naval and not self._footprint_close_enough_to_base(
top_left_x, top_left_y, width, height, base_cells, CHECK_FOR_WATER_RADIUS
):
return False
for dx in range(width):
for dy in range(height):
cell = (top_left_x + dx, top_left_y + dy)
if cell in occupied:
return False
if is_naval:
if not self._is_water_candidate_cell(*cell):
return False
else:
if not self._is_passable_cell(*cell):
return False
if self._resource_amount_at(*cell) > 0.0:
return False
return True
def _schedule_next_build_check(self, obs: OpenRAObservation, active: bool):
delay = STRUCTURE_PRODUCTION_ACTIVE_DELAY if active else STRUCTURE_PRODUCTION_INACTIVE_DELAY
random_bonus = random.randrange(STRUCTURE_PRODUCTION_RANDOM_BONUS_DELAY) if STRUCTURE_PRODUCTION_RANDOM_BONUS_DELAY > 0 else 0
self._next_build_check_tick = obs.tick + delay + random_bonus
def _structure_queue_type(self, item_type: str) -> str:
canonical = self._canonical_building_type(item_type)
return "Defense" if canonical in DEFENSE_STRUCTURE_TYPES else "Building"
def _clear_queue_backoff(self, queue_type: str):
self._placement_backoff_until.pop(queue_type, None)
self._placement_backoff_snapshot.pop(queue_type, None)
def _queue_backoff_active(self, queue_type: str, obs: OpenRAObservation) -> bool:
until = self._placement_backoff_until.get(queue_type, -9999)
if until <= obs.tick:
self._clear_queue_backoff(queue_type)
return False
snapshot = self._placement_backoff_snapshot.get(queue_type)
if snapshot is not None:
prev_buildings, prev_conyards = snapshot
current_conyards = sum(1 for b in obs.buildings if b.type == "fact")
if len(obs.buildings) < prev_buildings or current_conyards > prev_conyards:
self._clear_queue_backoff(queue_type)
return False
return True
def _structure_queue_available(self, obs: OpenRAObservation, item_type: str) -> bool:
canonical = self._canonical_building_type(item_type)
if canonical in NAVAL_STRUCTURE_TYPES and not self._can_safely_build_naval_structure(obs):
return False
return not self._queue_backoff_active(self._structure_queue_type(canonical), obs)
def _priority_structure_reservation(self, obs: OpenRAObservation) -> int:
if self._build_index < len(BUILD_ORDER):
return self._pending_build_cost(obs)
power_balance = obs.economy.power_provided - obs.economy.power_drained
minimum_excess_power = self._minimum_excess_power_target(obs)
power_item = self._best_power_building(obs)
if power_balance < minimum_excess_power and power_item and self._structure_queue_available(obs, power_item):
return self._build_cost(power_item)
if not self._has_adequate_refinery_count(obs) and self._can_produce(obs, "proc") and self._structure_queue_available(obs, "proc"):
return self._build_cost("proc")
if self._expansion_refinery_pending(obs) and self._can_produce(obs, "proc") and self._structure_queue_available(obs, "proc"):
return self._build_cost("proc")
if self._in_recovery_mode(obs):
bldg_counts = self._building_counts(obs)
if (
bldg_counts.get("proc", 0) == 0
and not self._base_under_pressure(obs)
and self._can_produce(obs, "proc")
and self._structure_queue_available(obs, "proc")
):
return self._build_cost("proc")
return 0
def _rewind_build_order_after_cancel(self, obs: OpenRAObservation, item_type: str):
canonical = self._canonical_building_type(item_type)
for idx, placeholder in enumerate(BUILD_ORDER):
resolved = self._resolve_build_item(obs, placeholder)
if resolved is None:
continue
if self._canonical_building_type(resolved) != canonical:
continue
existing = self._building_counts(obs).get(canonical, 0)
required = sum(
1
for p in BUILD_ORDER[: idx + 1]
if (rp := self._resolve_build_item(obs, p)) is not None and self._canonical_building_type(rp) == canonical
)
if existing < required:
self._build_index = min(self._build_index, idx)
return
def _placement_anchor(
self,
obs: OpenRAObservation,
item_type: str,
fallback: Tuple[int, int],
) -> Tuple[int, int]:
if item_type == "proc":
plan = self._best_refinery_plan(obs)
if plan is not None:
return plan["anchor"]
return fallback
def _placement_candidates(
self,
obs: OpenRAObservation,
item_type: str,
cx: int,
cy: int,
min_radius: int,
max_radius: int,
) -> list[tuple[int, int]]:
if item_type in NAVAL_STRUCTURE_TYPES:
naval_candidates = self._naval_build_candidates(obs, item_type)
if naval_candidates:
return naval_candidates
occupied = self._occupied_building_cells(obs)
buildable_area = self._buildable_area_cells(obs)
candidates: list[tuple[int, int]] = []
w, h = self._get_map_size()
for radius in range(min_radius, max_radius + 1):
for dx in range(-radius, radius + 1):
for dy in range(-radius, radius + 1):
if max(abs(dx), abs(dy)) != radius:
continue
x = cx + dx
y = cy + dy
if x < 0 or y < 0 or x >= w or y >= h:
continue
candidates.append((x, y))
fitting = [
c for c in candidates
if self._candidate_fits_building_footprint(obs, item_type, c[0], c[1], occupied, buildable_area)
]
if fitting:
candidates = fitting
return candidates
def _resource_patch_threat(self, obs: OpenRAObservation, patch: dict[str, float | int]) -> int:
px = int(patch.get("resource_center_x", patch["center_x"]))
py = int(patch.get("resource_center_y", patch["center_y"]))
enemies = 0
for enemy in obs.visible_enemies:
if self._cell_distance(enemy.cell_x, enemy.cell_y, px, py) <= RESOURCE_PATCH_THREAT_RADIUS:
enemies += 1
for building in obs.visible_enemy_buildings:
if self._cell_distance(building.cell_x, building.cell_y, px, py) <= RESOURCE_PATCH_THREAT_RADIUS:
enemies += 2
return enemies
def _patch_target(self, patch: dict[str, float | int]) -> tuple[int, int]:
return (
int(patch.get("resource_center_x", patch["center_x"])),
int(patch.get("resource_center_y", patch["center_y"])),
)
def _nearest_patch_state(
self,
patch_states: list[dict[str, object]],
x: int,
y: int,
radius: int,
allow_fallback: bool = False,
) -> Optional[dict[str, object]]:
best: Optional[dict[str, object]] = None
best_dist = radius + 1
for state in patch_states:
tx, ty = state["target"] # type: ignore[index]
dist = self._cell_distance(x, y, tx, ty)
if dist <= radius and dist < best_dist:
best = state
best_dist = dist
if best is None and allow_fallback and patch_states:
best = min(
patch_states,
key=lambda state: self._cell_distance(x, y, state["target"][0], state["target"][1]), # type: ignore[index]
)
return best
def _resource_patch_states(self, obs: OpenRAObservation) -> list[dict[str, object]]:
patch_states: list[dict[str, object]] = []
refineries = [b for b in obs.buildings if b.type == "proc"]
conyards = [b for b in obs.buildings if b.type == "fact"]
base_center = self._base_center(obs)
anchors = [
(
conyard.cell_x if conyard.cell_x > 0 else conyard.pos_x // 1024,
conyard.cell_y if conyard.cell_y > 0 else conyard.pos_y // 1024,
)
for conyard in conyards
]
if not anchors and base_center is not None:
anchors = [base_center]
for idx, patch in enumerate(self._resource_patches):
target = self._patch_target(patch)
memory = self._patch_memory(patch)
nearest_refinery_distance = self._nearest_distance_to_buildings(target[0], target[1], refineries)
nearby_refineries = sum(
1
for refinery in refineries
if self._cell_distance(
target[0],
target[1],
refinery.cell_x if refinery.cell_x > 0 else refinery.pos_x // 1024,
refinery.cell_y if refinery.cell_y > 0 else refinery.pos_y // 1024,
)
<= RESOURCE_PATCH_REFINERY_DISLIKE_RADIUS
)
anchor_distance = self._nearest_anchor_distance(target[0], target[1], anchors)
base_distance = (
self._cell_distance(target[0], target[1], base_center[0], base_center[1])
if base_center is not None
else anchor_distance
)
patch_states.append(
{
"id": idx,
"patch": patch,
"target": target,
"harvesters": [],
"harvester_count": 0,
"refinery_count": 0,
"nearby_refineries": nearby_refineries,
"nearest_refinery_distance": nearest_refinery_distance,
"anchor_distance": anchor_distance,
"base_distance": base_distance,
"threat": self._resource_patch_threat(obs, patch),
"depletion_ratio": float(memory.get("depletion_ratio", 0.0)),
"depletion_trend": float(memory.get("depletion_trend", 0.0)),
"travel_cost": 0,
"capacity": 0,
"saturation": 0.0,
"lack": 0,
"density_score": 0,
"score": 0,
"refinery_score": 0,
"expansion_score": 0,
}
)
if not patch_states:
return patch_states
for refinery in refineries:
rx = refinery.cell_x if refinery.cell_x > 0 else refinery.pos_x // 1024
ry = refinery.cell_y if refinery.cell_y > 0 else refinery.pos_y // 1024
state = self._nearest_patch_state(
patch_states,
rx,
ry,
HARVESTER_REASSIGN_REFINERY_RADIUS,
allow_fallback=True,
)
if state is not None:
state["refinery_count"] = int(state["refinery_count"]) + 1
state["nearest_refinery_distance"] = min(
int(state["nearest_refinery_distance"]),
self._cell_distance(rx, ry, state["target"][0], state["target"][1]), # type: ignore[index]
)
for harvester in [u for u in obs.units if u.type == "harv"]:
state = self._nearest_patch_state(
patch_states,
harvester.cell_x,
harvester.cell_y,
HARVESTER_PATCH_ASSIGN_RADIUS,
allow_fallback=True,
)
if state is None:
forced_target = self._harvester_patch_targets.get(harvester.actor_id)
if forced_target is not None:
state = self._nearest_patch_state(
patch_states,
forced_target[0],
forced_target[1],
HARVESTER_PATCH_ASSIGN_RADIUS * 2,
allow_fallback=True,
)
if state is not None:
state["harvesters"].append(harvester) # type: ignore[index]
for state in patch_states:
patch = state["patch"] # type: ignore[assignment]
harvester_count = len(state["harvesters"]) # type: ignore[arg-type]
cells = int(patch["cells"]) # type: ignore[index]
total_density = float(patch["total_density"]) # type: ignore[index]
threat = int(state["threat"])
refinery_count = int(state["refinery_count"])
nearby_refineries = int(state["nearby_refineries"])
nearest_refinery_distance = min(
int(state["nearest_refinery_distance"]),
RESOURCE_PATCH_REFINERY_DISLIKE_RADIUS * 3,
)
anchor_distance = int(state["anchor_distance"])
base_distance = int(state["base_distance"])
depletion_ratio = float(state["depletion_ratio"])
depletion_trend = float(state["depletion_trend"])
capacity = self._resource_patch_capacity(
total_density,
cells,
refinery_count,
depletion_ratio,
threat,
)
if capacity > harvester_count:
lack = capacity - harvester_count
elif capacity < harvester_count:
lack = -(harvester_count - capacity)
else:
lack = 0
if refinery_count <= 0 and lack > 0:
lack = min(lack, 1)
if threat > 0 and lack > 0:
lack = 0
saturation = harvester_count / max(1, capacity) if capacity > 0 else float(harvester_count)
travel_cost = nearest_refinery_distance if refineries else anchor_distance + 8
if refinery_count <= 0 and refineries:
travel_cost = min(travel_cost + 4, anchor_distance + 10)
density_score = int(total_density * 8) + cells * 24
depletion_penalty = int(depletion_ratio * 400) + int(depletion_trend * 320)
support_bonus = refinery_count * 350
if refineries:
support_bonus += max(
0,
RESOURCE_PATCH_REFINERY_DISLIKE_RADIUS
- min(nearest_refinery_distance, RESOURCE_PATCH_REFINERY_DISLIKE_RADIUS),
) * 14
score = density_score + support_bonus
score -= threat * 240
score -= travel_cost * 12
score -= depletion_penalty
if harvester_count == 0 and refinery_count > 0 and threat == 0:
score += 90
if saturation > 1.0:
score -= int((saturation - 1.0) * 300)
refinery_score = density_score
refinery_score -= anchor_distance * 16
refinery_score -= nearby_refineries * 600
refinery_score -= threat * 220
refinery_score -= depletion_penalty
if nearby_refineries == 0:
refinery_score += 250
if refineries:
refinery_score += min(nearest_refinery_distance, RESOURCE_PATCH_REFINERY_DISLIKE_RADIUS) * 20
if threat == 0 and saturation >= 0.75:
refinery_score += 80
expansion_score = density_score
expansion_score -= base_distance * 6
expansion_score -= threat * 240
expansion_score -= depletion_penalty
if nearby_refineries == 0:
expansion_score += 120
if anchor_distance > MCV_FRIENDLY_CONYARD_DISLIKE_RANGE:
expansion_score += 100
if nearest_refinery_distance > MCV_FRIENDLY_REFINERY_DISLIKE_RANGE:
expansion_score += 80
if saturation >= 1.0 and threat == 0:
expansion_score += 60
state["harvester_count"] = harvester_count
state["capacity"] = capacity
state["saturation"] = saturation
state["travel_cost"] = travel_cost
state["lack"] = lack
state["density_score"] = density_score
state["score"] = score
state["refinery_score"] = refinery_score
state["expansion_score"] = expansion_score
return patch_states
def _can_reassign_harvester(self, obs: OpenRAObservation, harvester: UnitInfoModel) -> bool:
if obs.tick < self._harvester_retreat_until.get(harvester.actor_id, -9999):
return False
if obs.tick < self._harvester_reassign_until.get(harvester.actor_id, -9999):
return False
if self._harvester_recently_damaged(obs, harvester.actor_id):
return False
if obs.tick < self._harvester_no_resource_until.get(harvester.actor_id, -9999):
return False
if self._nearest_enemy_to_unit(obs, harvester, HARVESTER_THREAT_RADIUS) is not None:
return False
activity = harvester.current_activity.lower()
if "dock" in activity:
return False
return True
def _reassign_low_effect_harvesters(
self,
obs: OpenRAObservation,
) -> tuple[list[CommandModel], set[int]]:
if obs.tick - self._last_harvester_reassign_tick < LOW_EFFECT_HARVESTER_SCAN_INTERVAL:
return [], set()
self._last_harvester_reassign_tick = obs.tick
if self._base_under_pressure(obs) or len(self._resource_patches) < 2:
return [], set()
patch_states = self._resource_patch_states(obs)
donors = [state for state in patch_states if int(state["lack"]) < 0]
receivers = [
state
for state in patch_states
if int(state["lack"]) > 0 and int(state["threat"]) == 0
]
if not donors or not receivers:
fallback_donors = [
state
for state in patch_states
if int(state["harvester_count"]) > 1 and int(state["threat"]) == 0 and float(state["saturation"]) >= 1.0
]
if not receivers or not fallback_donors:
return [], set()
best_receiver = max(receivers, key=lambda state: int(state["score"]))
donors = [
state
for state in fallback_donors
if int(best_receiver["score"]) > int(state["score"]) + 600
]
if not donors:
return [], set()
for donor in donors:
donor["lack"] = min(int(donor["lack"]), -1)
donors.sort(key=lambda state: int(state["lack"]))
receivers.sort(
key=lambda state: (
int(state["score"]),
int(state["lack"]),
-int(state["travel_cost"]),
),
reverse=True,
)
commands: list[CommandModel] = []
redirected: set[int] = set()
for receiver in receivers:
need = int(receiver["lack"])
if int(receiver["refinery_count"]) <= 0:
need = min(need, 1)
if need <= 0:
continue
tx, ty = receiver["target"] # type: ignore[index]
for donor in donors:
if need <= 0 or int(donor["lack"]) >= 0:
continue
harvesters = sorted(
donor["harvesters"], # type: ignore[index]
key=lambda u: self._cell_distance(u.cell_x, u.cell_y, tx, ty),
)
for harvester in harvesters:
if need <= 0 or int(donor["lack"]) >= 0:
break
if harvester.actor_id in redirected:
continue
if not self._can_reassign_harvester(obs, harvester):
continue
if self._harvester_patch_targets.get(harvester.actor_id) == (tx, ty):
continue
commands.append(
CommandModel(
action=ActionType.HARVEST,
actor_id=harvester.actor_id,
target_x=tx,
target_y=ty,
)
)
redirected.add(harvester.actor_id)
donor["lack"] = int(donor["lack"]) + 1
need -= 1
self._harvester_patch_targets[harvester.actor_id] = (tx, ty)
self._harvester_reassign_until[harvester.actor_id] = obs.tick + HARVESTER_REASSIGN_COOLDOWN
self._harvester_last_progress_tick[harvester.actor_id] = obs.tick
self._log(
f"Redirecting harv #{harvester.actor_id} -> patch ({tx},{ty}) "
f"from overloaded patch {donor['target']}"
)
return commands, redirected
def _best_refinery_plan(
self,
obs: OpenRAObservation,
) -> Optional[dict[str, Tuple[int, int]]]:
patch_states = self._resource_patch_states(obs)
if not patch_states:
return None
conyards = [b for b in obs.buildings if b.type == "fact"]
if not conyards:
return None
requested = self._current_requested_refinery(obs)
if requested is not None:
request_id, anchor, target = requested
return {
"anchor": anchor,
"target": target,
"request_id": request_id,
} # type: ignore[return-value]
best: Optional[tuple[int, Tuple[int, int], Tuple[int, int]]] = None
for conyard in conyards:
anchor = (
conyard.cell_x if conyard.cell_x > 0 else conyard.pos_x // 1024,
conyard.cell_y if conyard.cell_y > 0 else conyard.pos_y // 1024,
)
for state in patch_states:
target = state["target"] # type: ignore[index]
dist = self._cell_distance(anchor[0], anchor[1], target[0], target[1])
if dist > BASE_BUILD_MAX_RADIUS + RESOURCE_PATCH_SEARCH_MARGIN:
continue
if int(state["nearby_refineries"]) >= MAX_REFINERIES_PER_PATCH:
continue
score = int(state["refinery_score"]) - dist * 8
if int(state["threat"]) == 0 and float(state["depletion_ratio"]) < 0.6:
score += 60
if best is None or score > best[0]:
best = (score, anchor, target)
if best is None:
conyard = conyards[0]
anchor = (
conyard.cell_x if conyard.cell_x > 0 else conyard.pos_x // 1024,
conyard.cell_y if conyard.cell_y > 0 else conyard.pos_y // 1024,
)
state = min(
patch_states,
key=lambda s: self._cell_distance(anchor[0], anchor[1], s["target"][0], s["target"][1]), # type: ignore[index]
)
return {"anchor": anchor, "target": state["target"]} # type: ignore[return-value]
return {"anchor": best[1], "target": best[2]}
def _best_expansion_patch_target(self, obs: OpenRAObservation) -> Optional[Tuple[int, int]]:
patch_states = self._resource_patch_states(obs)
if not patch_states:
return None
conyards = [b for b in obs.buildings if b.type == "fact"]
refineries = [b for b in obs.buildings if b.type == "proc"]
active_targets = list(self._mcv_targets.values())
best: Optional[tuple[int, Tuple[int, int]]] = None
for state in patch_states:
target = state["target"] # type: ignore[index]
if conyards and self._nearest_distance_to_buildings(target[0], target[1], conyards) < MCV_FRIENDLY_CONYARD_DISLIKE_RANGE:
continue
if refineries and self._nearest_distance_to_buildings(target[0], target[1], refineries) < MCV_FRIENDLY_REFINERY_DISLIKE_RANGE:
continue
if any(
self._cell_distance(target[0], target[1], active_target[0], active_target[1]) < MCV_FRIENDLY_CONYARD_DISLIKE_RANGE
for active_target in active_targets
):
continue
if int(state["threat"]) > 0:
continue
score = int(state["expansion_score"])
if float(state["depletion_ratio"]) >= 0.8:
score -= 200
if int(state["harvester_count"]) == 0 and int(state["capacity"]) >= 2:
score += 80
if best is None or score > best[0]:
best = (score, target)
return None if best is None or best[0] <= 0 else best[1]
def _naval_build_candidates(
self,
obs: OpenRAObservation,
item_type: str,
occupied: Optional[set[tuple[int, int]]] = None,
) -> list[tuple[int, int]]:
center = self._placement_base_center(obs) or (0, 0)
w, h = self._get_map_size()
if not self._spatial_raw:
return []
occupied = occupied or self._occupied_building_cells(obs)
buildable_area = self._buildable_area_cells(obs)
width, height = self._building_dimensions(item_type)
candidates: set[tuple[int, int]] = set()
origins = [
self._building_top_left(building)
for building in obs.buildings
if self._canonical_building_type(building.type) not in NO_BUILDABLE_AREA_TYPES
]
for ox, oy in origins:
for dx in range(-NAVAL_WATER_SCAN_RADIUS, NAVAL_WATER_SCAN_RADIUS + 1, NAVAL_WATER_SCAN_STRIDE):
for dy in range(-NAVAL_WATER_SCAN_RADIUS, NAVAL_WATER_SCAN_RADIUS + 1, NAVAL_WATER_SCAN_STRIDE):
if dx * dx + dy * dy > NAVAL_WATER_SCAN_RADIUS * NAVAL_WATER_SCAN_RADIUS:
continue
x = ox + dx
y = oy + dy
if x < 0 or y < 0 or x + width > w or y + height > h:
continue
candidate_center = (x + width // 2, y + height // 2)
center_radius = max(abs(candidate_center[0] - center[0]), abs(candidate_center[1] - center[1]))
if center_radius < BASE_BUILD_MIN_RADIUS or center_radius > NAVAL_BUILD_MAX_RADIUS:
continue
if not self._candidate_fits_building_footprint(
obs,
item_type,
x,
y,
occupied=occupied,
base_cells=buildable_area,
):
continue
candidates.add((x, y))
ordered = list(candidates)
ordered.sort(
key=lambda p: (
-self._naval_anchor_score(item_type, p[0], p[1]),
self._cell_distance(p[0], p[1], center[0], center[1]),
)
)
return ordered
def _naval_anchor_score(self, item_type: str, top_left_x: int, top_left_y: int) -> int:
width, height = self._building_dimensions(item_type)
center_x = top_left_x + width // 2
center_y = top_left_y + height // 2
return self._local_water_score(center_x, center_y, 2)
def _naval_gate_open_water_windows(self, obs: OpenRAObservation) -> int:
if not self._spatial_raw:
return 0
# Count only footprint-valid naval anchors with enough surrounding water.
candidates = self._naval_build_candidates(obs, "spen")
if not candidates:
return 0
viable = [
candidate
for candidate in candidates
if self._naval_anchor_score("spen", candidate[0], candidate[1]) >= NAVAL_MIN_WATER_SCORE
]
return min(len(viable), NAVAL_MIN_OPEN_WATER_WINDOWS)
def _best_naval_anchor(self, obs: OpenRAObservation) -> Optional[Tuple[int, int]]:
candidates = [
candidate
for candidate in self._naval_build_candidates(obs, "spen")
if self._naval_anchor_score("spen", candidate[0], candidate[1]) >= NAVAL_MIN_WATER_SCORE
]
if len(candidates) < NAVAL_CANDIDATE_MIN_COUNT:
return None
return candidates[0]
def _can_safely_build_naval_structure(self, obs: OpenRAObservation) -> bool:
if obs.tick < self._naval_disabled_until:
return False
if obs.tick - self._last_naval_gate_tick <= NAVAL_GATE_CACHE_TICKS:
return self._cached_naval_gate_ok
if any(self._canonical_building_type(b.type) in NAVAL_STRUCTURE_TYPES for b in obs.buildings):
self._naval_retry_buildable_count = -1
self._cached_naval_gate_ok = True
self._last_naval_gate_tick = obs.tick
return True
elif self._naval_retry_buildable_count >= 0:
if self._buildable_area_structure_count(obs) <= self._naval_retry_buildable_count:
self._cached_naval_gate_ok = False
self._last_naval_gate_tick = obs.tick
return False
self._naval_retry_buildable_count = -1
# Human-like: only enable naval when there is a strong, footprint-valid
# naval anchor near our current buildable area.
if self._naval_gate_open_water_windows(obs) < NAVAL_MIN_OPEN_WATER_WINDOWS:
self._cached_naval_gate_ok = False
self._last_naval_gate_tick = obs.tick
return False
ok = self._best_naval_anchor(obs) is not None
self._cached_naval_gate_ok = ok
self._last_naval_gate_tick = obs.tick
return ok
def _minimum_excess_power_target(self, obs: OpenRAObservation) -> int:
bonus = EXCESS_POWER_INCREMENT * (len(obs.buildings) // max(1, EXCESS_POWER_INCREASE_THRESHOLD))
return max(MINIMUM_EXCESS_POWER, min(MAXIMUM_EXCESS_POWER, MINIMUM_EXCESS_POWER + bonus))
def _has_any_production_building(self, obs: OpenRAObservation) -> bool:
return any(self._canonical_building_type(b.type) in PRODUCTION_BUILDING_TYPES for b in obs.buildings)
def _optimal_refinery_count(self, obs: OpenRAObservation) -> int:
target = INITIAL_MIN_REFINERY_COUNT
if self._has_any_production_building(obs):
target += ADDITIONAL_MIN_REFINERY_COUNT
return target
def _has_adequate_refinery_count(self, obs: OpenRAObservation) -> bool:
refinery_count = sum(1 for b in obs.buildings if b.type == "proc")
has_power = any(b.type in {"powr", "apwr"} for b in obs.buildings)
has_conyard = any(b.type == "fact" for b in obs.buildings)
return (
refinery_count >= self._optimal_refinery_count(obs)
or not has_power
or not has_conyard
)
def _best_power_building(self, obs: OpenRAObservation) -> Optional[str]:
for item in ("apwr", "powr"):
if self._can_produce(obs, item) and self._structure_queue_available(obs, item):
return item
return None
def _best_production_building(self, obs: OpenRAObservation) -> Optional[str]:
candidates = []
counts = self._building_counts(obs)
for item in ("weap", "barr", "tent"):
if not self._can_produce(obs, item):
continue
if not self._structure_queue_available(obs, item):
continue
limit = BUILDING_LIMITS.get(item)
if limit is not None and counts.get(item, 0) >= limit:
continue
candidates.append(item)
if not candidates:
return None
return random.choice(candidates)
def _preferred_early_naval_building(self, obs: OpenRAObservation, credits: int) -> Optional[str]:
if self._in_recovery_mode(obs):
return None
if any(self._canonical_building_type(b.type) in NAVAL_STRUCTURE_TYPES for b in obs.buildings):
return None
if not any(b.type == "proc" for b in obs.buildings):
return None
if not any(b.type in WAR_FACTORY_TYPES for b in obs.buildings):
return None
if not self._can_safely_build_naval_structure(obs):
return None
anchor = self._best_naval_anchor(obs)
if anchor is None or self._naval_anchor_score("spen", anchor[0], anchor[1]) < NAVAL_EARLY_BUILD_WATER_SCORE:
return None
naval_item = self._best_naval_production_building(obs)
if naval_item is None:
return None
if credits < self._build_cost(naval_item) + NAVAL_EARLY_BUILD_CREDIT_BUFFER:
return None
return naval_item
def _best_naval_production_building(self, obs: OpenRAObservation) -> Optional[str]:
candidates = []
counts = self._building_counts(obs)
for item in NAVAL_STRUCTURE_TYPES:
if not self._can_produce(obs, item):
continue
if not self._structure_queue_available(obs, item):
continue
limit = BUILDING_LIMITS.get(item)
if limit is not None and counts.get(item, 0) >= limit:
continue
candidates.append(item)
if not candidates:
return None
return random.choice(candidates)
def _unit_at_limit(self, obs: OpenRAObservation, item_type: str) -> bool:
limit = UNIT_LIMITS.get(item_type)
if limit is None:
return False
current = sum(1 for u in obs.units if u.type == item_type)
current += sum(1 for p in obs.production if p.item == item_type)
current += self._requested_production_count(item_type)
return current >= limit
def _current_unit_count(self, obs: OpenRAObservation, item_type: str) -> int:
return sum(1 for u in obs.units if u.type == item_type)
def _queue_delay_active(self, obs: OpenRAObservation, queue_type: str) -> bool:
return obs.tick < self._queue_delay_until.get(queue_type, -9999)
def _unit_delay_active(self, obs: OpenRAObservation, item_type: str) -> bool:
return obs.tick < self._unit_delay_until.get(item_type, -9999)
def _mark_unit_trained(self, obs: OpenRAObservation, item_type: str, queue_type: str):
queue_delay = QUEUE_PRODUCTION_DELAYS.get(queue_type, 0)
if queue_delay > 0:
self._queue_delay_until[queue_type] = max(
self._queue_delay_until.get(queue_type, -9999),
obs.tick + queue_delay,
)
unit_delay = UNIT_PRODUCTION_DELAYS.get(item_type, 0)
if unit_delay > 0:
self._unit_delay_until[item_type] = max(
self._unit_delay_until.get(item_type, -9999),
obs.tick + unit_delay,
)
def _idle_base_unit_count(self, obs: OpenRAObservation, queue_type: Optional[str] = None) -> int:
base_center = self._base_center(obs)
if base_center is None:
return 0
count = 0
for unit in obs.units:
if unit.type in {"harv", "mcv"}:
continue
if not getattr(unit, "is_idle", False):
continue
if self._cell_distance(unit.cell_x, unit.cell_y, base_center[0], base_center[1]) > IDLE_BASE_UNIT_RADIUS:
continue
if queue_type is not None and self._queue_type_for_unit(unit.type) != queue_type:
continue
count += 1
return count
def _production_support_available(
self,
obs: OpenRAObservation,
item_type: str,
unit_counts: Optional[dict[str, int]] = None,
) -> bool:
if item_type in SHIP_TYPES:
return any(self._canonical_building_type(b.type) in NAVAL_STRUCTURE_TYPES for b in obs.buildings)
if unit_counts is None:
unit_counts = {}
for unit in obs.units:
unit_counts[unit.type] = unit_counts.get(unit.type, 0) + 1
for prod in obs.production:
unit_counts[prod.item] = unit_counts.get(prod.item, 0) + 1
for requested in self._unit_requests:
unit_counts[requested] = unit_counts.get(requested, 0) + 1
if item_type in PLANE_TYPES:
airfields = sum(1 for b in obs.buildings if self._canonical_building_type(b.type) == "afld")
if airfields <= 0:
return False
plane_count = sum(unit_counts.get(t, 0) for t in PLANE_TYPES)
return plane_count < airfields * AIRFIELD_PLANE_CAPACITY
if item_type in AIRCRAFT_TYPES - PLANE_TYPES:
helipads = sum(1 for b in obs.buildings if self._canonical_building_type(b.type) == "hpad")
if helipads <= 0:
return False
aircraft_count = sum(unit_counts.get(t, 0) for t in AIRCRAFT_TYPES - PLANE_TYPES)
return aircraft_count < helipads * HELIPAD_AIRCRAFT_CAPACITY
return True
def _economy_ready_for_tech(self, obs: OpenRAObservation) -> bool:
refinery_count = sum(1 for b in obs.buildings if b.type == "proc")
if refinery_count < 2:
return False
return self._harvester_target(obs) >= max(2, refinery_count)
def _harvester_target(self, obs: OpenRAObservation) -> int:
refinery_count = sum(1 for b in obs.buildings if b.type == "proc")
if refinery_count <= 0:
return 0
target = max(INITIAL_HARVESTERS, refinery_count)
return min(target, UNIT_LIMITS.get("harv", target))
def _should_delay_harvester_request(self, obs: OpenRAObservation, current_harvesters: int) -> bool:
return False
def _desired_unit_share(
self,
obs: OpenRAObservation,
item_type: str,
unit_counts: dict[str, int],
) -> int:
share = UNITS_TO_BUILD.get(item_type, 0)
if share <= 0:
return 0
queue_type = self._queue_type_for_unit(item_type)
if queue_type is not None and self._unit_delay_active(obs, item_type):
return 0
if not self._production_support_available(obs, item_type, unit_counts):
return 0
if item_type == "harv":
return share if unit_counts.get("harv", 0) < self._harvester_target(obs) else 0
return share
def _ensure_mcv_requests(self, obs: OpenRAObservation):
if not any(b.type in WAR_FACTORY_TYPES for b in obs.buildings):
return
mcvs = sum(1 for u in obs.units if u.type == "mcv")
conyards = sum(1 for b in obs.buildings if b.type == "fact")
if (conyards <= 0 and mcvs > 1) or (conyards > 0 and mcvs > 0):
return
pending = sum(1 for p in obs.production if p.item == "mcv") + self._requested_production_count("mcv")
if conyards + mcvs + pending >= self._desired_mcv_count(obs):
return
if pending > 0:
return
self._request_unit_production("mcv")
def _desired_mcv_count(self, obs: OpenRAObservation) -> int:
if self._available_credits(obs) >= BUILD_ADDITIONAL_MCV_CASH_AMOUNT:
return MINIMUM_CONSTRUCTION_YARD_COUNT + ADDITIONAL_CONSTRUCTION_YARD_COUNT
return MINIMUM_CONSTRUCTION_YARD_COUNT
def _expansion_refinery_pending(self, obs: OpenRAObservation) -> bool:
if self._expansion_refinery_goal <= 0:
return False
if obs.tick >= self._expansion_refinery_until_tick:
self._clear_expansion_refinery_need()
return False
current = sum(1 for b in obs.buildings if b.type == "proc")
current += sum(1 for p in obs.production if p.item == "proc")
if current >= self._expansion_refinery_goal:
self._clear_expansion_refinery_need()
return False
return True
def _remember_expansion_refinery_need(self, obs: OpenRAObservation):
current = sum(1 for b in obs.buildings if b.type == "proc")
current += sum(1 for p in obs.production if p.item == "proc")
self._expansion_refinery_goal = max(self._expansion_refinery_goal, current) + 1
self._expansion_refinery_until_tick = max(self._expansion_refinery_until_tick, obs.tick + 2400)
def _clear_expansion_refinery_need(self):
self._expansion_refinery_goal = 0
self._expansion_refinery_until_tick = -9999
def _remember_requested_refinery(
self,
obs: OpenRAObservation,
actor_id: int,
conyard_loc: Tuple[int, int],
resource_loc: Tuple[int, int],
):
self._requested_refineries[actor_id] = (conyard_loc, resource_loc, obs.tick + REQUESTED_REFINERY_TTL)
def _current_requested_refinery(
self,
obs: OpenRAObservation,
) -> Optional[tuple[int, Tuple[int, int], Tuple[int, int]]]:
refineries = [b for b in obs.buildings if b.type == "proc"]
for actor_id, (conyard_loc, resource_loc, expiry_tick) in list(self._requested_refineries.items()):
if expiry_tick <= obs.tick:
self._requested_refineries.pop(actor_id, None)
continue
if (
refineries
and self._nearest_distance_to_buildings(resource_loc[0], resource_loc[1], refineries)
< RESOURCE_PATCH_REFINERY_DISLIKE_RADIUS
):
self._requested_refineries.pop(actor_id, None)
continue
return actor_id, conyard_loc, resource_loc
return None
def _consume_requested_refinery(self, actor_id: int):
self._requested_refineries.pop(actor_id, None)
def _expansion_pressure(self, obs: OpenRAObservation) -> tuple[bool, bool]:
if self._pick_expansion_target(obs) is None:
return False, False
refinery_count = sum(1 for b in obs.buildings if b.type == "proc")
production_count = sum(
1
for b in obs.buildings
if self._canonical_building_type(b.type) in PRODUCTION_BUILDING_TYPES
)
if refinery_count < INITIAL_MIN_REFINERY_COUNT + ADDITIONAL_MIN_REFINERY_COUNT or production_count <= 0:
return False, False
tech_count = sum(
1
for b in obs.buildings
if self._canonical_building_type(b.type) in TECH_BUILDING_TYPES
)
tolerate_on_cash = self._available_credits(obs) // 12000
expand_now = (
production_count
+ tech_count
- random.choice(EXPANSION_TOLERATE_VALUES)
- tolerate_on_cash
>= refinery_count
)
force_undeploy_even_no_base = (
production_count
+ tech_count
- random.choice(FORCE_EXPANSION_TOLERATE_VALUES)
- tolerate_on_cash
>= refinery_count
)
return expand_now, force_undeploy_even_no_base
def _maybe_undeploy_conyard_for_expansion(self, obs: OpenRAObservation) -> Optional[CommandModel]:
if obs.tick - self._last_conyard_undeploy_tick < CONYARD_UNDEPLOY_COOLDOWN:
return None
if any(u.type == "mcv" for u in obs.units):
return None
expand_now, force_undeploy_even_no_base = self._expansion_pressure(obs)
if not expand_now:
return None
expansion_target = self._pick_expansion_target(obs)
if expansion_target is None:
return None
conyards = [b for b in obs.buildings if b.type == "fact"]
if len(conyards) <= 1 and not force_undeploy_even_no_base:
return None
movable_conyards = [
b for b in conyards
if not (getattr(b, "is_producing", False) and getattr(b, "producing_item", "") == "proc")
and obs.tick >= self._mcv_deploy_until.get(b.actor_id, -9999)
]
if not movable_conyards:
return None
movable_conyards.sort(
key=lambda b: (
self._cell_distance(
b.cell_x if b.cell_x > 0 else b.pos_x // 1024,
b.cell_y if b.cell_y > 0 else b.pos_y // 1024,
expansion_target[0],
expansion_target[1],
),
b.actor_id,
)
)
conyard = movable_conyards[0]
self._last_conyard_undeploy_tick = obs.tick
self._mcv_deploy_until[conyard.actor_id] = obs.tick + MCV_DEPLOY_COMMAND_COOLDOWN
self._log(f"Undeploying conyard #{conyard.actor_id} for expansion -> {expansion_target}")
return CommandModel(action=ActionType.DEPLOY, actor_id=conyard.actor_id)
def _mcv_deploy_top_left(self, cell_x: int, cell_y: int) -> tuple[int, int]:
return cell_x + MCV_DEPLOY_OFFSET[0], cell_y + MCV_DEPLOY_OFFSET[1]
def _mcv_cell_for_top_left(self, top_left_x: int, top_left_y: int) -> tuple[int, int]:
return top_left_x - MCV_DEPLOY_OFFSET[0], top_left_y - MCV_DEPLOY_OFFSET[1]
def _can_mcv_deploy_at(self, obs: OpenRAObservation, cell_x: int, cell_y: int) -> bool:
top_left_x, top_left_y = self._mcv_deploy_top_left(cell_x, cell_y)
return self._candidate_fits_building_footprint(obs, "fact", top_left_x, top_left_y)
def _best_mcv_deploy_target(
self,
obs: OpenRAObservation,
mcv: UnitInfoModel,
expansion_target: Tuple[int, int],
) -> Optional[Tuple[int, int]]:
candidates = self._placement_candidates(
obs,
"fact",
expansion_target[0],
expansion_target[1],
MCV_MIN_DEPLOY_RADIUS,
MCV_MAX_DEPLOY_RADIUS,
)
if not candidates:
return None
source = (mcv.cell_x, mcv.cell_y)
deploy_cells = [self._mcv_cell_for_top_left(x, y) for x, y in candidates]
deploy_cells.sort(
key=lambda cell: (
abs(self._cell_distance(cell[0], cell[1], expansion_target[0], expansion_target[1]) - MCV_TRY_MAINTAIN_RANGE),
self._cell_distance(cell[0], cell[1], source[0], source[1]),
self._cell_distance(cell[0], cell[1], expansion_target[0], expansion_target[1]),
)
)
return deploy_cells[0]
def _pick_expansion_target(self, obs: OpenRAObservation) -> Optional[Tuple[int, int]]:
patch_target = self._best_expansion_patch_target(obs)
if patch_target is not None:
return patch_target
patch_states = self._resource_patch_states(obs)
fallback_patch_states = [
state
for state in patch_states
if int(state["threat"]) == 0
and float(state["depletion_ratio"]) < 0.9
]
if fallback_patch_states:
best_state = max(
fallback_patch_states,
key=lambda state: (
int(state["expansion_score"]),
int(state["capacity"]),
-int(state["base_distance"]),
),
)
if int(best_state["expansion_score"]) > -200:
return best_state["target"] # type: ignore[return-value]
conyards = [b for b in obs.buildings if b.type == "fact"]
refineries = [b for b in obs.buildings if b.type == "proc"]
candidates = self._search_grid(obs)
for target in candidates:
if self._nearest_distance_to_buildings(target[0], target[1], conyards) < MCV_FRIENDLY_CONYARD_DISLIKE_RANGE:
continue
if refineries and self._nearest_distance_to_buildings(target[0], target[1], refineries) < MCV_FRIENDLY_REFINERY_DISLIKE_RANGE:
continue
return target
return candidates[0] if candidates else None
def _nearest_distance_to_buildings(self, x: int, y: int, buildings: list[BuildingInfoModel]) -> int:
if not buildings:
return 10**9
return min(
self._cell_distance(
x,
y,
b.cell_x if b.cell_x > 0 else b.pos_x // 1024,
b.cell_y if b.cell_y > 0 else b.pos_y // 1024,
)
for b in buildings
)
def _cell_distance(self, ax: int, ay: int, bx: int, by: int) -> int:
return abs(ax - bx) + abs(ay - by)
def _queue_type_for_unit(self, item_type: str) -> Optional[str]:
if item_type == "mcv":
return "Vehicle"
for queue_type, allowed in UNIT_QUEUE_ORDER:
if item_type in allowed:
return queue_type
return None
def _roll_assault_threshold(self) -> int:
return SQUAD_SIZE + random.randrange(SQUAD_SIZE_RANDOM_BONUS)
def _select_squad_leader(self, squad_units: list[UnitInfoModel]) -> UnitInfoModel:
avg_x = sum(u.cell_x for u in squad_units) / len(squad_units)
avg_y = sum(u.cell_y for u in squad_units) / len(squad_units)
return min(squad_units, key=lambda u: (u.cell_x - avg_x) ** 2 + (u.cell_y - avg_y) ** 2)
def _attack_wave_units(
self,
obs: OpenRAObservation,
squad_units: list[UnitInfoModel],
) -> list[UnitInfoModel]:
return squad_units
def _regroup_squad_commands(
self,
squad_units: list[UnitInfoModel],
leader: UnitInfoModel,
regroup_radius: int = REGROUP_RADIUS,
min_close_units: Optional[int] = None,
circular: bool = False,
) -> List[CommandModel]:
def within_radius(unit: UnitInfoModel) -> bool:
dx = unit.cell_x - leader.cell_x
dy = unit.cell_y - leader.cell_y
if circular:
return dx * dx + dy * dy <= regroup_radius * regroup_radius
return self._cell_distance(unit.cell_x, unit.cell_y, leader.cell_x, leader.cell_y) <= regroup_radius
close_units = [
u for u in squad_units
if within_radius(u)
]
if min_close_units is None:
min_close_units = max(2, int(len(squad_units) * 0.4))
if len(close_units) >= min_close_units:
return []
commands = [CommandModel(action=ActionType.STOP, actor_id=leader.actor_id)]
redirected = 0
for u in squad_units:
if u.actor_id == leader.actor_id:
continue
if not within_radius(u):
commands.append(CommandModel(
action=ActionType.ATTACK_MOVE,
actor_id=u.actor_id,
target_x=leader.cell_x,
target_y=leader.cell_y,
))
redirected += 1
if redirected:
self._log(f"Regrouping {redirected}/{len(squad_units)} units around leader")
return commands
return []
def _visible_enemy_units_near(
self,
obs: OpenRAObservation,
x: int,
y: int,
radius: int,
) -> list[UnitInfoModel]:
return [
e for e in obs.visible_enemies
if self._cell_distance(x, y, e.cell_x, e.cell_y) <= radius
]
def _visible_enemy_buildings_near(
self,
obs: OpenRAObservation,
x: int,
y: int,
radius: int,
) -> list[BuildingInfoModel]:
return [
b for b in obs.visible_enemy_buildings
if self._cell_distance(x, y, b.cell_x, b.cell_y) <= radius
]
def _estimate_combat_power(self, actor) -> float:
base = UNIT_COMBAT_POWER.get(actor.type, 0)
if base == 0:
base = BUILDING_THREAT_POWER.get(actor.type, 0)
if base == 0:
return 0.0
hp = getattr(actor, "hp_percent", 1.0)
speed = getattr(actor, "speed", 0)
attack_range = getattr(actor, "attack_range", 0)
return base * max(0.2, hp) * (1.0 + min(speed / 200.0, 0.25) + min(attack_range / 12000.0, 0.25))
def _building_can_attack(self, building: BuildingInfoModel) -> bool:
return (
self._canonical_building_type(building.type) in ATTACKING_BUILDING_TYPES
and getattr(building, "is_powered", True)
)
def _actor_cell(self, actor) -> Tuple[int, int]:
if getattr(actor, "cell_x", 0) > 0 or getattr(actor, "cell_y", 0) > 0:
return actor.cell_x, actor.cell_y
return actor.pos_x // 1024, actor.pos_y // 1024
def _attack_or_flee_rules(self, rush: bool) -> tuple[tuple[tuple[str, ...], tuple[str, ...], tuple[str, ...], tuple[str, ...], str], ...]:
return FUZZY_RUSH_RULES if rush else FUZZY_DEFAULT_RULES
def _fuzzy_trapezoid(self, value: float, left: float, left_top: float, right_top: float, right: float) -> float:
if value <= left or value >= right:
if (value == left == left_top) or (value == right == right_top):
return 1.0
return 0.0
if left_top <= value <= right_top:
return 1.0
if value < left_top:
if left_top == left:
return 1.0
return (value - left) / (left_top - left)
if right == right_top:
return 1.0
return (right - value) / (right - right_top)
def _fuzzy_input_membership(self, variable: str, term: str, value: float) -> float:
if variable in {"OwnHealth", "EnemyHealth"}:
shapes = {
"NearDead": (0.0, 0.0, 20.0, 40.0),
"Injured": (30.0, 50.0, 50.0, 70.0),
"Normal": (50.0, 80.0, 100.0, 100.0),
}
else:
shapes = {
"Weak": (0.0, 0.0, 70.0, 90.0),
"Equal": (85.0, 100.0, 100.0, 115.0),
"Strong": (110.0, 150.0, 150.0, 1000.0),
"Slow": (0.0, 0.0, 70.0, 90.0),
"Fast": (110.0, 150.0, 150.0, 1000.0),
}
left, left_top, right_top, right = shapes[term]
return self._fuzzy_trapezoid(value, left, left_top, right_top, right)
def _fuzzy_output_membership(self, term: str, value: float) -> float:
shapes = {
"Attack": (0.0, 15.0, 15.0, 30.0),
"Flee": (25.0, 35.0, 35.0, 50.0),
}
left, left_top, right_top, right = shapes[term]
return self._fuzzy_trapezoid(value, left, left_top, right_top, right)
def _normalized_health(self, actors: list) -> float:
if not actors:
return 0.0
return max(0.0, min(100.0, 100.0 * sum(max(0.0, getattr(actor, "hp_percent", 1.0)) for actor in actors) / len(actors)))
def _attack_power_metric(self, actors: list) -> float:
total = 0.0
for actor in actors:
if isinstance(actor, UnitInfoModel):
if actor.can_attack:
total += UNIT_COMBAT_POWER.get(actor.type, 0)
elif isinstance(actor, BuildingInfoModel) and self._building_can_attack(actor):
total += BUILDING_THREAT_POWER.get(actor.type, 0)
return total
def _speed_metric(self, actors: list) -> float:
speeds = [max(0, getattr(actor, "speed", 0)) for actor in actors if isinstance(actor, UnitInfoModel) and getattr(actor, "speed", 0) > 0]
if not speeds:
return 0.0
return sum(speeds) / len(speeds)
def _relative_metric(self, own_value: float, enemy_value: float) -> float:
if enemy_value <= 0:
return 999.0 if own_value > 0 else 100.0
if own_value <= 0:
return 0.0
return max(0.0, min(999.0, own_value / enemy_value * 100.0))
def _attack_or_flee_score(self, own_actors: list, enemy_actors: list, rush: bool) -> Optional[float]:
inputs = {
"OwnHealth": self._normalized_health(own_actors),
"EnemyHealth": self._normalized_health(enemy_actors),
"RelativeAttackPower": self._relative_metric(
self._attack_power_metric(own_actors),
self._attack_power_metric(enemy_actors),
),
"RelativeSpeed": self._relative_metric(
self._speed_metric(own_actors),
self._speed_metric(enemy_actors),
),
}
activation = {"Attack": 0.0, "Flee": 0.0}
for own_terms, enemy_terms, power_terms, speed_terms, outcome in self._attack_or_flee_rules(rush):
degree = min(
max(self._fuzzy_input_membership("OwnHealth", term, inputs["OwnHealth"]) for term in own_terms),
max(self._fuzzy_input_membership("EnemyHealth", term, inputs["EnemyHealth"]) for term in enemy_terms),
max(self._fuzzy_input_membership("RelativeAttackPower", term, inputs["RelativeAttackPower"]) for term in power_terms),
max(self._fuzzy_input_membership("RelativeSpeed", term, inputs["RelativeSpeed"]) for term in speed_terms),
)
activation[outcome] = max(activation[outcome], degree)
if activation["Attack"] <= 0.0 and activation["Flee"] <= 0.0:
return None
numerator = 0.0
denominator = 0.0
for sample in range(101):
value = sample * 0.5
membership = max(
min(activation["Attack"], self._fuzzy_output_membership("Attack", value)),
min(activation["Flee"], self._fuzzy_output_membership("Flee", value)),
)
numerator += value * membership
denominator += membership
if denominator <= 0.0:
return None
return numerator / denominator
def _attack_or_flee_can_attack(self, own_actors: list, enemy_actors: list, rush: bool) -> bool:
score = self._attack_or_flee_score(own_actors, enemy_actors, rush)
return score is not None and score < 30.0
def _select_rush_target(
self,
obs: OpenRAObservation,
rush_units: list[UnitInfoModel],
) -> Optional[Tuple[int, int, int, str]]:
attackable_units = [
unit for unit in rush_units
if unit.can_attack and unit.type not in AIRCRAFT_TYPES | SHIP_TYPES
]
if not attackable_units:
return None
sample_unit = random.choice(attackable_units)
conyards = [
building for building in obs.visible_enemy_buildings
if self._canonical_building_type(building.type) == "fact"
]
conyards.sort(key=lambda building: self._cell_distance(sample_unit.cell_x, sample_unit.cell_y, *self._actor_cell(building)))
for conyard in conyards:
cx, cy = self._actor_cell(conyard)
defenders: list = [
enemy
for enemy in obs.visible_enemies
if enemy.can_attack
and enemy.type not in AIRCRAFT_TYPES | SHIP_TYPES
and self._cell_distance(enemy.cell_x, enemy.cell_y, cx, cy) <= RUSH_ATTACK_SCAN_RADIUS
]
defenders.extend(
building
for building in obs.visible_enemy_buildings
if building.actor_id != conyard.actor_id
and self._building_can_attack(building)
and self._cell_distance(*self._actor_cell(building), cx, cy) <= RUSH_ATTACK_SCAN_RADIUS
)
if not self._attack_or_flee_can_attack(attackable_units, defenders, rush=True):
continue
target = random.choice(defenders) if defenders else conyard
target_kind = "unit" if isinstance(target, UnitInfoModel) else "building"
tx, ty = self._actor_cell(target)
return tx, ty, target.actor_id, target_kind
return None
def _should_take_local_fight(
self,
squad_units: list[UnitInfoModel],
enemy_units: list[UnitInfoModel],
enemy_buildings: list[BuildingInfoModel],
rush: bool,
cautious: bool = False,
squad_name: str = "assault",
) -> bool:
own_units = [u for u in squad_units if u.can_attack]
if not own_units:
return False
if squad_name in {"assault", "rush"}:
enemy_actors = list(enemy_units) + list(enemy_buildings)
if cautious and self._normalized_health(own_units) < 55.0:
return False
return self._attack_or_flee_can_attack(own_units, enemy_actors, rush=rush)
own_power = sum(self._estimate_combat_power(u) for u in own_units)
enemy_power = (
sum(self._estimate_combat_power(u) for u in enemy_units)
+ sum(self._estimate_combat_power(b) * 0.7 for b in enemy_buildings)
)
own_avg_hp = sum(u.hp_percent for u in own_units) / max(1, len(own_units))
enemy_avg_hp = (
sum(u.hp_percent for u in enemy_units) + sum(b.hp_percent for b in enemy_buildings)
) / max(1, len(enemy_units) + len(enemy_buildings))
own_avg_speed = sum(max(1, getattr(u, "speed", 1)) for u in own_units) / max(1, len(own_units))
enemy_avg_speed = sum(max(1, getattr(u, "speed", 1)) for u in enemy_units) / max(1, len(enemy_units))
if enemy_power <= 1:
return True
power_ratio = own_power / enemy_power
speed_ratio = own_avg_speed / max(1.0, enemy_avg_speed)
required_ratio = 1.05
min_hp = 0.48
if squad_name == "protection":
required_ratio = 0.92
min_hp = 0.4
elif squad_name == "rush":
required_ratio = 1.0
min_hp = 0.55
elif squad_name in {"air", "naval"}:
required_ratio = 1.08
min_hp = 0.5
if rush:
required_ratio = min(required_ratio, 1.04)
if cautious:
required_ratio += 0.12
min_hp = max(min_hp, 0.5)
if own_avg_hp < RETREAT_HEALTH_THRESHOLD:
required_ratio += 0.18
elif own_avg_hp >= enemy_avg_hp:
required_ratio -= 0.08
if speed_ratio < 0.9 and squad_name not in {"air", "rush"}:
required_ratio += 0.05
if squad_name == "air" and any(b.type in {"sam", "agun", "tsla"} for b in enemy_buildings):
required_ratio += 0.15
if squad_name == "naval" and enemy_buildings:
required_ratio += 0.08
if squad_name != "protection" and any(b.type in {"tsla", "gun", "ftur", "agun"} for b in enemy_buildings):
required_ratio += 0.08
if not enemy_units and not any(b.type in DEFENSE_STRUCTURE_TYPES | {"agun", "sam"} for b in enemy_buildings):
required_ratio -= 0.1
required_ratio = max(0.82, required_ratio)
return own_avg_hp >= min_hp and power_ratio >= required_ratio
def _pick_priority_target(
self,
obs: OpenRAObservation,
x: Optional[int],
y: Optional[int],
local_only: bool,
squad_name: str = "assault",
) -> Optional[Tuple[int, int, int, str, str]]:
best: Optional[Tuple[float, Tuple[int, int, int, str, str]]] = None
local_radius = LOCAL_FIGHT_RADIUS + (4 if squad_name in {"air", "naval"} else 0)
for b in obs.visible_enemy_buildings:
if local_only and x is not None and y is not None and self._cell_distance(x, y, b.cell_x, b.cell_y) > local_radius:
continue
priority = TARGET_BUILDING_PRIORITY.get(b.type, 40)
if squad_name == "protection":
priority += 8 if b.type in DEFENSE_STRUCTURE_TYPES else -12
elif squad_name == "rush":
if b.type in {"proc", "weap", "fact", "powr", "apwr"}:
priority += 12
elif squad_name == "air":
if b.type in {"proc", "weap", "fact", "powr", "apwr", "hpad", "afld", "afld.ukraine"}:
priority += 14
if b.type in {"sam", "agun", "tsla"}:
priority -= 25
elif squad_name == "naval":
if b.type in NAVAL_STRUCTURE_TYPES | {"proc", "weap"}:
priority += 10
if b.type in {"sam", "agun", "tsla"}:
priority -= 10
dist = self._cell_distance(x, y, b.cell_x, b.cell_y) if x is not None and y is not None else 0
score = priority * 1000 - dist * 20 + (1.0 - b.hp_percent) * 120
candidate = (b.actor_id, b.cell_x, b.cell_y, b.type, "building")
if best is None or score > best[0]:
best = (score, candidate)
for e in obs.visible_enemies:
if local_only and x is not None and y is not None and self._cell_distance(x, y, e.cell_x, e.cell_y) > local_radius:
continue
if "husk" in e.type:
continue
if not e.can_attack and e.type not in {"harv", "mcv"} and squad_name not in {"rush", "air"}:
continue
priority = TARGET_UNIT_PRIORITY.get(e.type, 30 if e.can_attack else 10)
if squad_name == "protection":
if e.can_attack:
priority += 15
if e.type in {"harv", "mcv"}:
priority -= 20
elif squad_name == "rush":
if e.type in {"harv", "mcv", "arty", "v2rl"}:
priority += 10
elif squad_name == "air":
if e.type in {"harv", "mcv", "arty", "v2rl", "ftrk"}:
priority += 14
elif squad_name == "naval":
if e.type in SHIP_TYPES:
priority += 18
elif e.type in AIRCRAFT_TYPES:
priority -= 10
dist = self._cell_distance(x, y, e.cell_x, e.cell_y) if x is not None and y is not None else 0
score = priority * 1000 - dist * 25 + (1.0 - e.hp_percent) * 150
candidate = (e.actor_id, e.cell_x, e.cell_y, e.type, "unit")
if best is None or score > best[0]:
best = (score, candidate)
return best[1] if best is not None else None
def _pick_closest_visible_target(
self,
obs: OpenRAObservation,
x: Optional[int],
y: Optional[int],
squad_name: str = "assault",
) -> Optional[Tuple[int, int, int, str, str]]:
if x is None or y is None:
return self._pick_priority_target(obs, x, y, local_only=False, squad_name=squad_name)
best: Optional[Tuple[tuple[int, int, int], Tuple[int, int, int, str, str]]] = None
for b in obs.visible_enemy_buildings:
priority = TARGET_BUILDING_PRIORITY.get(b.type, 40)
if squad_name == "protection":
priority += 8 if b.type in DEFENSE_STRUCTURE_TYPES else -12
elif squad_name == "rush" and b.type in {"proc", "weap", "fact", "powr", "apwr"}:
priority += 12
elif squad_name == "air":
if b.type in {"proc", "weap", "fact", "powr", "apwr", "hpad", "afld", "afld.ukraine"}:
priority += 14
if b.type in {"sam", "agun", "tsla"}:
priority -= 25
elif squad_name == "naval":
if b.type in NAVAL_STRUCTURE_TYPES | {"proc", "weap"}:
priority += 10
if b.type in {"sam", "agun", "tsla"}:
priority -= 10
dist = self._cell_distance(x, y, b.cell_x, b.cell_y)
key = (dist, -priority, -int((1.0 - b.hp_percent) * 100))
candidate = (b.actor_id, b.cell_x, b.cell_y, b.type, "building")
if best is None or key < best[0]:
best = (key, candidate)
for e in obs.visible_enemies:
if "husk" in e.type:
continue
if not e.can_attack and e.type not in {"harv", "mcv"} and squad_name not in {"rush", "air"}:
continue
priority = TARGET_UNIT_PRIORITY.get(e.type, 30 if e.can_attack else 10)
if squad_name == "protection":
if e.can_attack:
priority += 15
if e.type in {"harv", "mcv"}:
priority -= 20
elif squad_name == "rush" and e.type in {"harv", "mcv", "arty", "v2rl"}:
priority += 10
elif squad_name == "air" and e.type in {"harv", "mcv", "arty", "v2rl", "ftrk"}:
priority += 14
elif squad_name == "naval":
if e.type in SHIP_TYPES:
priority += 18
elif e.type in AIRCRAFT_TYPES:
priority -= 10
dist = self._cell_distance(x, y, e.cell_x, e.cell_y)
key = (dist, -priority, -int((1.0 - e.hp_percent) * 100))
candidate = (e.actor_id, e.cell_x, e.cell_y, e.type, "unit")
if best is None or key < best[0]:
best = (key, candidate)
return best[1] if best is not None else None
def _target_actor_is_visible(
self,
obs: OpenRAObservation,
target_actor_id: int,
target_kind: str,
) -> bool:
return self._visible_actor_by_target(obs, target_actor_id, target_kind) is not None
def _focus_fire_commands(
self,
squad_units: list[UnitInfoModel],
target: Tuple[int, int, int, str, str],
) -> List[CommandModel]:
target_actor_id, tx, ty, _, target_kind = target
commands = []
for u in squad_units:
if not u.can_attack or self._busy_attacking(u):
continue
commands.append(CommandModel(
action=ActionType.ATTACK,
actor_id=u.actor_id,
target_actor_id=target_actor_id,
target_x=tx,
target_y=ty,
))
if commands:
self._record_attack_issue(
direct_attack=True,
command_count=len(commands),
target_actor_id=target_actor_id,
target_kind=target_kind,
)
return commands
def _record_attack_issue(
self,
direct_attack: bool,
command_count: int,
target_actor_id: int = 0,
target_kind: str = "point",
) -> None:
if command_count <= 0:
return
if direct_attack:
self._attack_commands_issued += command_count
else:
self._attack_move_commands_issued += command_count
if target_actor_id <= 0:
return
if target_kind == "unit":
self._unit_target_events += 1
self._unique_unit_targets.add(target_actor_id)
elif target_kind == "building":
self._building_target_events += 1
self._unique_building_targets.add(target_actor_id)
def get_attack_stats(self, obs: Optional[OpenRAObservation] = None) -> dict[str, int]:
stats = {
"attack_commands": self._attack_commands_issued,
"attack_move_commands": self._attack_move_commands_issued,
"unit_target_events": self._unit_target_events,
"building_target_events": self._building_target_events,
"unique_unit_targets": len(self._unique_unit_targets),
"unique_building_targets": len(self._unique_building_targets),
}
if obs is not None:
stats["units_killed"] = obs.military.units_killed
stats["buildings_killed"] = obs.military.buildings_killed
return stats
def get_squad_stats(self) -> dict[str, object]:
return {
"idle_ground": len(self._idle_ground_units),
"attack_squad": len(self._attack_squad),
"rush_squad": len(self._rush_squad),
"protection_squad": len(self._protection_squad),
"air_squad": len(self._air_squad),
"naval_squad": len(self._naval_squad),
"assault_threshold": self._assault_threshold,
"states": dict(self._squad_states),
"targets": {name: self._squad_target_point[name] for name in self._squad_target_point},
}
def _busy_attacking(self, unit: UnitInfoModel) -> bool:
if unit.is_idle:
return False
activity = getattr(unit, "current_activity", "").lower().replace(" ", "")
if not activity or "attackmove" in activity:
return False
return "attack" in activity
def _retreat_squad_commands(
self,
obs: OpenRAObservation,
squad_units: list[UnitInfoModel],
leader: UnitInfoModel,
) -> List[CommandModel]:
fallback = self._pick_retreat_point(obs, leader)
if fallback is None:
return []
tx, ty = fallback
return [
CommandModel(
action=ActionType.MOVE,
actor_id=u.actor_id,
target_x=tx,
target_y=ty,
)
for u in squad_units
]
def _pick_retreat_point(
self,
obs: OpenRAObservation,
leader: UnitInfoModel,
) -> Optional[Tuple[int, int]]:
if not obs.buildings:
return self._base_center(obs)
type_bonus = {
"fact": 420,
"weap": 280,
"proc": 260,
"ftur": 220,
"gun": 200,
"tsla": 220,
"pbox": 140,
"hbox": 140,
"powr": 90,
"apwr": 110,
}
best_score: Optional[int] = None
best_pos: Optional[Tuple[int, int]] = None
for building in obs.buildings:
bx = building.cell_x if building.cell_x > 0 else building.pos_x // 1024
by = building.cell_y if building.cell_y > 0 else building.pos_y // 1024
leader_dist = self._cell_distance(leader.cell_x, leader.cell_y, bx, by)
enemy_clearance = min(
[self._cell_distance(enemy.cell_x, enemy.cell_y, bx, by) for enemy in obs.visible_enemies] + [LOCAL_FIGHT_RADIUS + 8]
)
static_clearance = min(
[self._cell_distance(enemy.cell_x, enemy.cell_y, bx, by) for enemy in obs.visible_enemy_buildings] + [LOCAL_FIGHT_RADIUS + 8]
)
canonical = self._canonical_building_type(building.type)
score = type_bonus.get(canonical, 80)
score += min(enemy_clearance, LOCAL_FIGHT_RADIUS + 8) * 18
score += min(static_clearance, LOCAL_FIGHT_RADIUS + 8) * 10
score -= leader_dist * 8
if canonical in DEFENSE_STRUCTURE_TYPES:
score += 40
if best_score is None or score > best_score:
best_score = score
best_pos = (bx, by)
return best_pos or self._base_center(obs)
def _has_own_building_near(self, obs: OpenRAObservation, x: int, y: int, radius: int) -> bool:
return any(
self._cell_distance(
building.cell_x if building.cell_x > 0 else building.pos_x // 1024,
building.cell_y if building.cell_y > 0 else building.pos_y // 1024,
x,
y,
) <= radius
for building in obs.buildings
)
def _credits_str(self, obs: OpenRAObservation) -> str:
return (
f"${obs.economy.cash} cash + ${obs.economy.ore} ore"
f" = ${self._available_credits(obs)}"
)
def _can_produce(self, obs: OpenRAObservation, item_type: str) -> bool:
if item_type in obs.available_production:
return True
for b in obs.buildings:
if item_type in b.can_produce:
return True
return False
def _log(self, msg: str):
if self.verbose:
print(f" [NormalAI] {msg}")
|