File size: 1,843 Bytes
cc6e5ac | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | from __future__ import annotations
import numpy as np
INITIAL_DETECTION_LEVEL = 0.3
INITIAL_ENERGY = 1.0
INITIAL_FATIGUE = 0.0
VALUE_RANGE = (0.0, 1.0)
DETECTION_DECAY = 0.97
FATIGUE_GAIN_THRESHOLD = 0.7
FATIGUE_GAIN_MULTIPLIER = 0.5
B_CELL_TRANSITIONS = {
"INCREASE_HIGH": {"detection_delta": 0.15, "energy_delta": -0.20, "fatigue_delta": 0.10},
"INCREASE_LOW": {"detection_delta": 0.08, "energy_delta": -0.10, "fatigue_delta": 0.04},
"MAINTAIN": {"detection_delta": 0.0, "energy_delta": -0.03, "fatigue_delta": 0.0},
"REDUCE": {"detection_delta": -0.10, "energy_delta": 0.18, "fatigue_delta": -0.12},
}
def _clip_unit(value: float) -> float:
return float(np.clip(value, *VALUE_RANGE))
class BCellAgent:
def __init__(self) -> None:
self.reset()
def reset(self) -> None:
self.detection_level = _clip_unit(INITIAL_DETECTION_LEVEL)
self.energy = _clip_unit(INITIAL_ENERGY)
self.fatigue = _clip_unit(INITIAL_FATIGUE)
def step(self, action: str) -> None:
transition = B_CELL_TRANSITIONS.get(action, B_CELL_TRANSITIONS["MAINTAIN"])
detection_delta = float(transition["detection_delta"])
if self.fatigue > FATIGUE_GAIN_THRESHOLD and detection_delta > 0.0:
detection_delta *= FATIGUE_GAIN_MULTIPLIER
self.detection_level = _clip_unit(self.detection_level * DETECTION_DECAY)
self.detection_level = _clip_unit(self.detection_level + detection_delta)
self.energy = _clip_unit(self.energy + float(transition["energy_delta"]))
self.fatigue = _clip_unit(self.fatigue + float(transition["fatigue_delta"]))
def get_state(self) -> dict:
return {
"detection_level": float(self.detection_level),
"energy": float(self.energy),
"fatigue": float(self.fatigue),
}
|