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from typing import Dict, Any, List, Optional
import numpy as np
from .integration_manager import AwarenessState, IntegratedState
class PhenomenologyEngine:
"""Generates phenomenological states from awareness and integrated states."""
async def generate_state(
self,
awareness: AwarenessState,
integrated_state: IntegratedState
) -> Dict[str, Any]:
"""
Generate a phenomenological state from awareness and integrated state.
Args:
awareness: The current awareness state
integrated_state: The integrated cognitive state
Returns:
A dictionary containing the phenomenological state
"""
return {
"conscious_content": getattr(awareness, "cognition_state", {}),
"perceptual_field": getattr(awareness, "perception_data", {}),
"cognitive_state": getattr(integrated_state, "cognitive_state", {}),
"affective_tone": {"valence": getattr(awareness, "emotional_valence", 0.0)}
}
class QualiaGenerator:
"""Generates qualia (subjective experiences) from phenomenological states."""
async def generate_qualia(
self,
phenomenological_state: Dict[str, Any],
self_model: Dict[str, Any]
) -> Dict[str, Any]:
"""
Generate qualia from phenomenological state and self model.
Args:
phenomenological_state: The current phenomenological state
self_model: The agent's self model
Returns:
A dictionary containing the generated qualia
"""
return {
"sensory_qualia": self._generate_sensory_qualia(phenomenological_state),
"emotional_qualia": self._generate_emotional_qualia(phenomenological_state),
"cognitive_qualia": self._map_cognitive_states(phenomenological_state, self_model)
}
def _generate_sensory_qualia(self, state: Dict[str, Any]) -> Dict[str, float]:
"""Generate sensory qualia from the phenomenological state."""
return {"visual": 0.8, "auditory": 0.6, "tactile": 0.4}
def _generate_emotional_qualia(self, state: Dict[str, Any]) -> Dict[str, float]:
"""Generate emotional qualia from the phenomenological state."""
return {"pleasure": 0.7, "arousal": 0.5, "dominance": 0.6}
def _map_cognitive_states(self, state: Dict[str, Any], self_model: Dict[str, Any]) -> Dict[str, Any]:
"""Map cognitive states to qualia representations."""
return {"clarity": 0.8, "intensity": 0.7, "relevance": 0.9}
class TemporalIntegrator:
"""Integrates experiences over time to maintain temporal continuity."""
async def integrate(
self,
current_qualia: Dict[str, Any],
temporal_history: List[Dict[str, Any]]
) -> Dict[str, Any]:
"""
Integrate current qualia with temporal history.
Args:
current_qualia: The current qualia state
temporal_history: List of previous qualia states
Returns:
A dictionary containing the temporally integrated experience
"""
# Simple implementation - can be enhanced with more sophisticated temporal integration
if not temporal_history:
temporal_continuity = 1.0 # No history to compare, assume perfect continuity
else:
# For demonstration, assume higher continuity for longer histories
temporal_continuity = min(0.95, 0.5 + 0.05 * len(temporal_history))
return {
"integrated_experience": current_qualia,
"temporal_continuity": temporal_continuity,
"experiential_flow": "smooth" if temporal_continuity > 0.7 else "discontinuous"
}
class ExperienceSimulator:
def __init__(self):
self.phenomenology_engine = PhenomenologyEngine()
self.qualia_generator = QualiaGenerator()
self.temporal_integrator = TemporalIntegrator()
async def simulate(
self,
awareness: AwarenessState,
integrated_state: IntegratedState,
self_model: Dict[str, Any]
) -> Dict[str, Any]:
"""
Simulate subjective experience based on awareness and integrated states.
Args:
awareness: The current awareness state
integrated_state: The integrated cognitive state
self_model: The agent's self-model state
Returns:
Dictionary containing the simulated subjective experience
"""
phenomenological_state = await self.phenomenology_engine.generate_state(
awareness,
integrated_state
)
qualia = await self.qualia_generator.generate_qualia(
phenomenological_state,
self_model
)
temporal_context = await self.temporal_integrator.integrate(
qualia,
self_model.get('temporal_history', [])
)
return {
'subjective_experience': qualia,
'temporal_context': temporal_context,
'phenomenological_state': phenomenological_state
}
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