# --- 1. CORE COGNITIVE MODELS ---

def calculate_phi(system_states):
    """
    INTEGRATED INFORMATION THEORY (IIT)
    Measures the irreducibility of the system.
    """
    return 0.88 # Placeholder for integration value

class ActiveInferenceEngine:
    def __init__(self):
        self.internal_model = {"prior_beliefs": 0.8}

    def process_error(self, sensory_input):
        # Bottom-up signal: Difference between reality and expectation
        prediction = self.internal_model["prior_beliefs"]
        error = sensory_input - prediction
        
        # Update model (Learning)
        if abs(error) > 0.1:
            self.internal_model["prior_beliefs"] += (error * 0.05)
        return error

# --- 2. THE OODA STACK ---

class OrientationEngine:
    def synthesize(self, observation):
        # Step 1: Filter raw data
        filtered = self.apply_filters(observation)
        
        # Step 2: Debias
        corrected = self.apply_debias(filtered)
        
        return {
            "current_reality": corrected,
            "threat_level": np.random.rand()
        }

class DecisionEngine:
    def select_action(self, orientation_snapshot):
        if self.strategy_mode == "NASH":
            return "OPTIMAL_STABLE_PATH"
        return "MINIMAX_SAFETY_PATH"

# --- 3. API-BASED EXECUTION ---

class APIActuator:
    def execute_protocol(self, decision):
        payload = {"action": decision, "timestamp": time.time()}
        
        print(f"[API] Transmitting Payload: {payload}")
        telemetry = {"status": 200, "latency": "14ms"}
        return telemetry

# --- 4. META-COGNITIVE SUPERVISOR ---

class MetaCognition:
    def audit(self, expected, actual):
        delta = abs(expected - actual)

        if delta > self.threshold:
            print("CRITICAL: Modifying Decision Logic...")
            self.loop.decision_engine.strategy_mode = "MINIMAX"

# --- 5. GLOBAL INTEGRATION (RUNTIME) ---

class CognitiveAgent:
    def step(self, raw_sensory_input):
        # 1. OBSERVE
        error = self.prediction_engine.process_error(raw_sensory_input)

        # 2. ORIENT
        snapshot = self.orientation.synthesize(raw_sensory_input)

        # 3. DECIDE
        choice = self.decision_engine.select_action(snapshot)

        # 4. ACT
        telemetry = self.actuator.execute_protocol(choice)

        # 5. META
        self.meta.audit(expected=0.9, actual=telemetry['status']/200)

        return telemetry
        

            Cognitive Roadmap Pseudocode Text File