work/Convergence_Engine/data/config.json

{
  "_case_study": "STUDY 6: BOOM-BUST WAVES - Grounded learning with periodic Highlander concentration",
  "_hypothesis": "Organisms that build foundations (6→26→76→276 words) before facing Highlander waves develop more coherent intelligence than those thrown into instant chaos",
  "_hardware_profile_help": "Set to 'beast', 'workstation', 'standard', 'laptop', 'potato', or 'cpu_only' to override auto-detection. null = auto-detect",
  "language": {
    "_help": "Grounded Language Mode: Organisms learn language through action-outcome associations before semantic understanding",
    "mode": "grounded",
    "_mode_options": "grounded | semantic | hybrid",
    "grounded": {
      "enabled": true,
      "mastery_gating": true,
      "vocabulary_masking": "soft",
      "_vocabulary_masking_options": "soft | hard | none",
      "initial_mastery_level": 0,
      "_initial_mastery_level_help": "0=6 words, 1=26 words, 2=76 words, 3=276 words, 4=10000 (semantic graduation)",
      "mastery_vocab_sizes": [6, 26, 76, 276, 10000],
      "mastery_advancement_ratio": 0.5,
      "mastery_depth_ratio": 0.3,
      "mastery_min_experiences": [25, 100, 300, 600],
      "always_allow_tokens": [".", ",", "!", "?", "and", "the", "a", "is", "to", "of", "in"]
    },
    "semantic": {
      "enabled": false,
      "knowledge_web_bootstrap": false,
      "semantic_reward_at_level_4": true,
      "semantic_reward_weight": 0.25
    },
    "action_hints": {
      "enabled": true,
      "bias_strength": 0.3,
      "expectation_window_seconds": 10.0
    },
    "organism_learning_berth": {
      "_help": "Bounded lane for learning from human-selected suggestions and operation-sequence prompts. Inside-game only; no outside command authority.",
      "enabled": true,
      "space_window_seconds": 3600,
      "config_window_seconds": 1200,
      "max_interaction_context_words": 64,
      "human_choice_reward_bonus": 0.08,
      "operation_sequence_reward_bonus": 0.05,
      "allowed_operation_axes": ["inside", "around", "above", "below", "between", "through"],
      "inside_boundary": "inside_game_only",
      "forbidden_outside_actions": ["deployment", "money", "identity", "safety_systems", "authority_override"]
    }
  },
  "agency": {
    "confidence_threshold": 0.0001,
    "decision_precision": 1e-05,
    "initial_mode": "manual_only",
    "learning_rate_resolution": 1e-06,
    "performance_tracking_precision": 0.0001
  },
  "semantic_convergence": {
    "_help": "Unifies 6 semantic systems for word embedding differentiation",
    "enabled": true,
    "use_learned_embeddings": true,
    "embedding_dim": 64,
    "organism_embedding_alpha": 0.15,
    "concept_system_alpha": 0.1,
    "knowledge_web_influence_interval": 10,
    "phenotype_to_vocabulary": true
  },
  "arena": {
    "_prefer_native_games_help": "When true, prioritizes language/concept games that use organism's native abilities (no Gym dependency)",
    "_proton_game_probability_help": "Fraction of battles that use Proton Game Arena (0.0-1.0). Set to 0.5 for 50% Proton Game battles.",
    "trap_mechanics": {
      "_help": "Planning pressure via trap logic in battles",
      "enabled": true,
      "low_foresight_threshold": 0.35,
      "high_foresight_threshold": 0.65,
      "trap_chance_multiplier": 0.4,
      "trap_damage_multiplier": 0.1
    },
    "battle_consequences": {
      "fitness_transfer_rate": 1,
      "resource_transfer_enabled": true,
      "resource_transfer_rate": 1,
      "trait_bonus_cap": 0.3,
      "trait_evolution_enabled": true
    },
    "default_battle_type": "PROTON_GAME",
    "description": "Proton Game Arena - Apprentice Adept style gym battles (Piers Anthony + Highlander inspired)",
    "enabled": true,
    "game_selection": {
      "allow_negotiation": true,
      "fallback_on_deadlock": "random",
      "mode": "ai_driven",
      "negotiation_rounds": 3
    },
    "grid_weights": {
      "challenge_types": {
        "ARTS": 2.0,
        "CHANCE": 1.0,
        "MENTAL": 1.5,
        "PHYSICAL": 0.5
      },
      "resource_types": {
        "ANIMAL": 1.0,
        "MACHINE": 1.0,
        "NAKED": 1.5,
        "TOOL": 1.0
      }
    },
    "gym_settings": {
      "default_episodes": 10,
      "max_episode_steps": 1000,
      "parallel_envs": 1,
      "render_mode": null
    },
    "prefer_native_games": false,
    "proton_game_probability": 1.0,
    "gym_only": true,
    "_gym_only_help": "When true, ONLY real Gymnasium environments (CartPole, Acrobot, etc). No native/custom games.",
    "tournament": {
      "default_format": "single_elimination",
      "round_robin_battles_per_pair": 3,
      "seeding_method": "fitness_based"
    }
  },
  "causation_detection": {
    "correlation_threshold": 0.5,
    "direct_causation_time_window": 2,
    "enable_bidirectional_causations": true,
    "enable_language_causations": true,
    "enable_ml_causations": true,
    "enable_neural_causations": true,
    "enable_neural_decision_causations": true,
    "enable_neural_training_causations": true,
    "enable_phase_transition_causations": true,
    "enabled": true,
    "phase_transition_time_window": 2.5,
    "recent_events_window": 150,
    "thresholds": {
      "clustering_coefficient": {
        "collapse": 0.5,
        "direction": "above"
      },
      "modularity": {
        "collapse": 0.3,
        "direction": "below"
      },
      "organism_count": {
        "collapse": 500,
        "direction": "above"
      },
      "violation_pressure": {
        "vp0": 0.25,
        "vp1": 0.5,
        "vp2": 0.75,
        "vp3": 0.99
      },
      "vp_calculations": {
        "direction": "above",
        "transition": 50
      }
    }
  },
  "evolution": {
    "adaptation_sensitivity": 0.005,
    "diversity_guard": {
      "enabled": true,
      "frequency_threshold": 0.1,
      "hash_similarity_threshold": 0.88,
      "penalty": 0.05
    },
    "fitness_precision": 1e-07,
    "genotype_length": 48,
    "max_generations": 1500,
    "mutation_rate": {
      "initial": 0.04
    },
    "mutation_rate_precision": 0.001,
    "population_size": 25
  },
  "feedback": {
    "enabled": true,
    "hysteresis_checks": 5,
    "interval_frames": 10,
    "knobs": {
      "clustering_bias": {
        "initial": 1.5,
        "max": 1.6,
        "min": 0.3,
        "step": 0.05
      },
      "mutation_rate": {
        "initial": 0.033,
        "max": 0.06,
        "min": 0.002,
        "step": 0.001
      },
      "new_edge_rate": {
        "initial": 4.8,
        "max": 6,
        "min": 0.2,
        "step": 0.1
      },
      "quantum_pruning": {
        "initial": 0.35,
        "max": 1,
        "min": 0,
        "step": 0.05
      }
    },
    "rate_limit_frames": 120
  },
  "hardware_profile": null,
  "hardware_governor": {
    "_auto_scale_help": "Set to false to disable auto-scaling of config values. Governor will only clamp to max, not scale up.",
    "auto_scale": false
  },
  "health_monitor": {
    "critical_threshold": 0.25,
    "enabled": true,
    "healthy_threshold": 0.75,
    "history_size": 100,
    "thresholds": {
      "critical": 0.25,
      "healthy": 0.65,
      "warning": 0.45
    },
    "warning_threshold": 0.55,
    "weight_adaptability": 0.2,
    "weight_coherence": 0.3,
    "weight_diversity": 0.25,
    "weight_lawfulness": 0.15,
    "weight_sustainability": 0.1
  },
  "highlander": {
    "eval_interval_seconds": 300,
    "_eval_interval_seconds_help": "Battle frequency for mastery 4+ organisms (seconds between Highlander rounds). Organisms below mastery 4 are protected regardless of this setting.",
    "alliance_warfare": {
      "betrayal_chance": 0.0,
      "confederation_war_threshold": 0.6,
      "enabled": true,
      "existential_war_threshold": 0.8,
      "max_alliance_size": 999,
      "max_alliances": 9999,
      "max_confederations": 9999,
      "min_alliance_size": 2,
      "war_declaration_threshold": 0.6,
      "war_frequency": 0.5,
      "illumination_stability_threshold": 5,
      "organism_communication": {
        "enabled": true,
        "_help": "Organisms speak to each other at confluence points (battles, alliances, etc.)",
        "pre_battle_communication": true,
        "communication_affects_battles": true,
        "intel_bonus_max": 0.15,
        "_intel_bonus_help": "Max reaction speed bonus from shared vocabulary in battles",
        "ultimatum_enabled": true,
        "_ultimatum_help": "Warchiefs can issue 'Join or Die' demands to weaker alliances"
      }
    },
    "chaos_factor": 0.0,
    "competition_intensity": 0.4,
    "concordance_contact_enabled": true,
    "_concordance_contact_enabled_help": "When allied-only Highlander pools would otherwise avoid contact, record bounded non-lethal concordance receipts instead of forcing domination.",
    "concordance_pressure_value": 1.0,
    "_concordance_pressure_value_help": "Semantic credit value split across participants for each concordance contact obligation.",
    "description": "BOOM-BUST WAVES: 10-minute growth → Highlander culling → regeneration → repeat. Selects for learning competence over chaos survival.",
    "enabled": true,
    "extreme_mode": {
      "chaos_factor": 0.0,
      "competition_intensity": 0.4,
      "description": "EXTREME DIFFICULTY - Maximum evolutionary pressure",
      "germination_rate": 0.1,
      "max_battle_rounds": 15,
      "max_population": 25,
      "min_population": 15,
      "mutation_rate": 0.0,
      "population_size": 200,
      "predation_enabled": true,
      "rounds_per_cycle": 2,
      "survival_threshold": 0.4
    },
    "germination_rate": 0.15,
    "max_battle_rounds": 30,
    "max_capsules": 100,
    "max_genetic_samples": 100,
    "max_population": 50,
    "min_population": 10,
    "mutation_rate": 0.0,
    "population_size": 200,
    "predation_enabled": true,
    "rounds_per_cycle": 3,
    "survival_threshold": 0.5
  },
  "lattice": {
    "entropy_sensitivity": 5e-05,
    "interaction_precision": 0.0001,
    "particles": 1000,
    "prune_threshold": 0,
    "stability_tolerance": 0.0005
  },
  "logging": {
    "shared_state_dump_interval": 30,
    "sample_rate": 5,
    "_sample_rate_help": "Log 1 in N state entries to disk (1=all, 10=10%). Memory history always full rate."
  },
  "meta_cognitive": {
    "description": "Meta-cognitive systems: self-awareness, self-tuning, autonomous optimization",
    "self_tuning": {
      "enabled": true,
      "min_confidence_threshold": 0.6,
      "mode": "autonomous",
      "performance_targets": {
        "max_anomaly_ratio": 0.2,
        "min_cluster_diversity": 3,
        "min_fitness_std": 0.05
      },
      "safe_parameters": [
        "evolution.mutation_rate.initial",
        "evolution.diversity_guard.penalty",
        "evolution.diversity_guard.frequency_threshold",
        "evolution.diversity_guard.hash_similarity_threshold",
        "evolution.population_size",
        "evolution.adaptation_sensitivity",
        "feedback.knobs.mutation_rate.initial",
        "feedback.knobs.new_edge_rate.initial",
        "feedback.knobs.clustering_bias.initial",
        "feedback.knobs.quantum_pruning.initial",
        "neural.training.learning_rate",
        "neural.training.gamma",
        "neural.training.epsilon_decay",
        "neural.training.batch_size",
        "neural.rewards.fitness_improvement",
        "neural.rewards.connection_success",
        "neural.rewards.survival",
        "neural.inheritance.crossover_rate",
        "neural.inheritance.mutation_rate",
        "network.max_organisms",
        "network.max_connections",
        "network.resource_pool",
        "scikit.clustering.min_cluster_size",
        "scikit.anomaly_detection.contamination",
        "scikit.anomaly_detection.n_estimators",
        "quantum.initial_states",
        "quantum.entanglement_sensitivity",
        "quantum.prune_check_interval",
        "vp_monitoring.adaptive_response.high_vp_threshold",
        "vp_monitoring.stabilization.smoothing_factor",
        "causation_detection.correlation_threshold",
        "meta_cognitive.self_tuning.tuning_interval_frames",
        "meta_cognitive.self_tuning.min_confidence_threshold"
      ],
      "tuning_interval_frames": 5
    }
  },
  "network": {
    "connection_strength_resolution": 5e-06,
    "emergence_sensitivity": 1e-06,
    "max_connections": 48000,
    "max_organisms": 5000,
    "resource_flow_precision": 0.0001,
    "resource_pool": 1000,
    "stability_precision": 1e-07
  },
  "neural": {
    "brain": {
      "activation": "relu",
      "dropout": 0.1,
      "hidden_dim": 64,
      "input_dim": 30,
      "output_dim": 6,
      "vocab_size": 10000,
      "attention_dim": 32
    },
    "hopfield": {
      "_help": "Modern continuous Hopfield network for iterative thought refinement",
      "enabled": true,
      "patterns": 32,
      "iterations": 5,
      "beta": 1.0
    },
    "world_model": {
      "_help": "Predictive world model for imagination-based planning",
      "enabled": true,
      "delta": 0.2,
      "_delta_help": "Loss weight for world model prediction (alpha+beta+gamma+delta should sum reasonably)",
      "curiosity_scale": 0.05,
      "_curiosity_scale_help": "How much prediction error contributes to intrinsic reward",
      "planning_trust": 0.25,
      "_planning_trust_help": "Blend factor: (1-trust)*DQN + trust*imagination",
      "imagination_temperature": 3.0,
      "_imagination_temperature_help": "Sharpness of imagination softmax (higher = more decisive)",
      "imagination_enabled": true,
      "candidate_threshold": 0.10,
      "_candidate_threshold_help": "Only imagine actions with base probability above this",
      "language_magnetism_weight": 0.15,
      "_language_magnetism_weight_help": "How much word magnetism biases imagination scoring",
      "max_imagination_steps": 5,
      "_max_imagination_steps_help": "Maximum planning horizon for high-foresight organisms",
      "foresight_scaling": true,
      "_foresight_scaling_help": "If true, steps = 1 + int(foresight * max_steps). If false, always use max_steps",
      "pruning_threshold": 0.15,
      "_pruning_threshold_help": "Skip imagining branches with cumulative probability below this",
      "discount_factor": 0.9,
      "_discount_factor_help": "Gamma for discounting future imagined rewards"
    },
    "concept_system": {
      "concept_loss_weight": 0.15,
      "embed_dim": 64,
      "enabled": true,
      "num_key_compositions": 30,
      "utility_update_alpha": 0.15
    },
    "device": "cuda",
    "enabled": true,
    "inheritance": {
      "crossover_rate": 0.9,
      "enabled": true,
      "mutation_rate": 0.2
    },
    "initialization": {
      "deterministic": false,
      "seed": null
    },
    "language_model": {
      "attention": {
        "attention_dim": 32,
        "enabled": true,
        "num_heads": 4
      },
      "curriculum": {
        "enabled": true,
        "ml_quality": {
          "enabled": true,
          "high_quality_threshold": 0.55,
          "low_quality_threshold": 0.3,
          "max_sequence_length": 64,
          "min_sequence_length": 8,
          "sequence_length_step": 2
        },
        "sequence_lengths": {
          "stage_0": 8,
          "stage_1": 16,
          "stage_2": 32,
          "stage_3": 128
        },
        "vp_thresholds": {
          "stage_1": 0.5,
          "stage_2": 0.4,
          "stage_3": 0.3
        }
      },
      "enabled": true,
      "generation": {
        "max_length": 128,
        "temperature": 1.5,
        "vp_gate_threshold": 0.5
      },
      "knowledge_web": {
        "embedding_dim": 64,
        "enabled": true,
        "max_concepts": 2400,
        "quality_control": {
          "confidence_growth_rate": 0.0008,
          "enabled": true,
          "exploration_decay_generations": 1000,
          "exploration_end": 0.08,
          "exploration_start": 0.3,
          "max_discoveries_per_generation": 15,
          "min_confidence_threshold": 0.25,
          "min_discovery_count": 3,
          "pruning_confidence_threshold": 0.2,
          "pruning_failure_rate": 0.7,
          "pruning_unused_generations": 100,
          "review_frequency": 100,
          "validation_required": true,
          "vp_boost_exploration": true,
          "vp_boost_threshold": 0.7
        }
      },
      "relationship_learning": {
        "enabled": true,
        "quality_evaluation": {
          "coherent_threshold": 0.45,
          "garbled_threshold": 0.25,
          "max_word_count": 25,
          "min_word_count": 2,
          "min_word_count_for_evaluation": 3,
          "relationship_strength_threshold": 0.4,
          "unk_ratio_threshold": 0.35
        },
        "semantic_guidance": {
          "enabled": true,
          "high_strength_boost": 0.2,
          "max_similar_words": 8,
          "min_strength_threshold": 0.25,
          "semantic_boost": 0.4
        }
      },
      "sequence": {
        "context_window": 32,
        "max_length": 128
      },
      "teacher": {
        "embedding_dim": 64,
        "enabled": true,
        "min_action_history": 3,
        "min_confidence": 0.25,
        "teaching_frequency": 1,
        "use_knowledge_web": true,
        "use_semantic_embeddings": true,
        "vocab_size": 50000,
        "staged_knowledge": {
          "_help": "Delay loading expanded knowledge web to let organisms build foundations with innate vocab first",
          "enabled": true,
          "delay_seconds": 0,
          "start_with_innate_only": true
        }
      },
      "training": {
        "alpha": 0.5,
        "beta": 0.4,
        "gamma": 0.1,
        "vp_temperature_scale": true,
        "entropy_bonus": 0.015,
        "label_smoothing": 0.12,
        "language_epsilon_start": 0.4,
        "language_epsilon_end": 0.08,
        "language_epsilon_decay": 0.996,
        "_entropy_bonus_help": "Higher entropy for creative specialist - encourages more diverse, creative output",
        "_label_smoothing_help": "Slightly higher smoothing for creative exploration",
        "_language_epsilon_help": "Higher language epsilon for creative specialist - more random token exploration encourages novel combinations."
      },
      "vocabulary": {
        "max_size": 10000,
        "special_tokens": [
          "<PAD>",
          "<UNK>",
          "<START>",
          "<END>",
          "<VP_GATE>"
        ]
      }
    },
    "optimization": {
      "amp": {
        "enabled": true,
        "dtype": "auto",
        "_dtype_help": "'auto' detects optimal dtype (BF16 for Ampere+, FP16 for older). Can also be 'float16' or 'bfloat16'",
        "description": "Mixed precision training - 2-3x GPU speedup on Tensor Core GPUs"
      },
      "compile_mode": "max-autotune",
      "reuse_optimizers": true,
      "use_compile": true,
      "use_scripted_inference": false
    },
    "rewards": {
      "connection_failure": -0.2,
      "connection_success": 2.5,
      "fitness_improvement": 4.5,
      "resource_gain": 1,
      "resource_loss": -0.3,
      "survival": 2
    },
    "training": {
      "batch_size": 64,
      "early_stopping": {
        "enabled": true,
        "min_delta": 0.0001,
        "patience": 10
      },
      "enabled": true,
      "epsilon": 0.95,
      "epsilon_decay": 0.99,
      "epsilon_end": 0.01,
      "epsilon_start": 0.8,
      "gamma": 0.995,
      "language_reward_scaling": 0.4,
      "learning_rate": 0.005,
      "lr_scheduler": {
        "enabled": true,
        "gamma": 0.95,
        "min_lr": 0.0001,
        "step_size": 100,
        "type": "cosine",
        "warmup_steps": 100
      },
      "memory_size": 50000,
      "update_frequency": 1
    },
    "vp_aware_planning": {
      "base_boost": 0.18,
      "enabled": true,
      "high_threshold": 0.45,
      "low_threshold": 0.25,
      "strong_boost": 0.3
    },
    "checkpointing": {
      "_help": "Auto-save training state to prevent data loss. Checkpoint every N generations or minutes.",
      "enabled": true,
      "auto_save_interval_generations": 100,
      "auto_save_interval_minutes": 30,
      "max_checkpoints": 5,
      "checkpoint_dir": "data/neural_checkpoints",
      "include_experience_buffer": false,
      "include_optimizer_states": true,
      "compression": true,
      "auto_resume": true
    }
  },
  "quantum": {
    "entanglement_sensitivity": 2.5e-06,
    "fitness_weights": {
      "entanglement": 0.3,
      "entropy": 0.2,
      "measurements": 0.25,
      "superposition": 0.25
    },
    "initial_states": 80,
    "performance_thresholds": {
      "fitness_std_threshold": 0.3,
      "iteration_time_ms": 10,
      "memory_percentage": 5.0,
      "min_fitness_to_keep": 0.1
    },
    "probability_precision": 1e-06,
    "prune_check_interval": 40,
    "superposition_tolerance": 0.0005
  },
  "ray": {
    "enabled": false,
    "actor_pool_size": 2,
    "batch_inference_size": 64,
    "description": "Ray DISABLED",
    "fallback_on_error": true,
    "logging_level": "warning",
    "memory_management": {
      "actor_pool_lru_eviction": true,
      "cleanup_on_organism_death": true,
      "max_object_refs": 100
    },
    "num_cpus": 4,
    "num_gpus": 1,
    "object_store_memory": null,
    "parallelization_threshold": 100,
    "state_synchronization": {
      "consistency_model": "sequential",
      "max_state_age_ms": 100,
      "snapshot_strategy": "breath_cycle"
    },
    "training_threshold": 16
  },
  "rendering": {
    "enable_visualizations": true,
    "frame_rate": 15,
    "metric_display_precision": 6,
    "mode": "god",
    "performance_monitoring": false,
    "render_quality": "low",
    "resolution": [
      1280,
      720
    ],
    "text_interface": true,
    "visualization_update_precision": 0.001
  },
  "scikit": {
    "anomaly_detection": {
      "algorithm": "isolation_forest",
      "contamination": 0.18,
      "enabled": true,
      "n_estimators": 450
    },
    "clustering": {
      "algorithm": "hdbscan",
      "enabled": true,
      "min_cluster_size": 4,
      "min_samples": 1,
      "use_neural_embeddings": true
    },
    "concept_tracking": {
      "enabled": true,
      "persistence_threshold": 3,
      "stale_threshold": 10
    },
    "dimensionality_reduction": {
      "algorithm": "pca",
      "enabled": true,
      "n_components": 3
    },
    "enabled": true
  },
  "simulation": {
    "log_level": "INFO",
    "max_runtime": 14400.0,
    "measurement_precision": 4,
    "performance_sampling_rate": 200,
    "save_interval": 60.0,
    "target_fps": 0,
    "_target_fps_help": "0 = unlimited speed, >0 = rate limit to N cycles/sec",
    "time_resolution_ms": 1.0
  },
  "vp_monitoring": {
    "adaptive_response": {
      "high_vp_threshold": 0.85,
      "streak_threshold": 3
    },
    "adaptive_thresholds": {
      "enabled": true
    },
    "adaptive_thresholds_enabled": true,
    "component_decomposition_enabled": true,
    "component_weights": {
      "evolution_pressure": 0.15,
      "network_coherence": 0.15,
      "phase_mismatch": 0.1,
      "quantum_entropy": 0.15,
      "trait_divergence": 0.15
    },
    "diagnostics_enabled": true,
    "stabilization": {
      "enabled": true,
      "history_size": 15,
      "max_jump": 0.1,
      "smoothing_factor": 0.4
    },
    "stabilization_enabled": true
  }
}