Spaces:
Sleeping
Sleeping
from enum import Enum | |
from dataclasses import dataclass | |
import numpy as np | |
from typing import Dict, List, Optional, Any | |
class ConsciousnessPhase(Enum): | |
PROTO = "proto_consciousness" | |
FUNCTIONAL = "functional_consciousness" | |
REFLECTIVE = "reflective_consciousness" | |
INTEGRATED = "integrated_consciousness" | |
class PhaseState: | |
phase: ConsciousnessPhase | |
stability: float | |
integration_level: float | |
awareness_metrics: Dict[str, float] | |
class ConsciousnessEmergence: | |
def __init__(self): | |
self.current_phase = ConsciousnessPhase.PROTO | |
self.phase_history = [] | |
self.awareness_threshold = 0.7 | |
self.integration_threshold = 0.8 | |
def evaluate_phase_transition(self, system_state: Dict[str, Any]) -> Optional[ConsciousnessPhase]: | |
current_metrics = self._compute_phase_metrics(system_state) | |
if self._should_transition(current_metrics): | |
return self._determine_next_phase(current_metrics) | |
return None | |
def _compute_phase_metrics(self, system_state: Dict[str, Any]) -> Dict[str, float]: | |
# Implementation needed | |
return {} | |
def _should_transition(self, metrics: Dict[str, float]) -> bool: | |
# Implementation needed | |
return False | |
def _determine_next_phase(self, metrics: Dict[str, float]) -> ConsciousnessPhase: | |
# Implementation needed | |
return self.current_phase | |