Consciousness / applied epistemiology
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#!/usr/bin/env python3
"""
QUANTUM APPLIED EPISTEMOLOGY ENGINE - lm_quant_veritas v7.0
----------------------------------------------------------------
Operationalizing the process of understanding understanding itself.
Advanced recursive epistemology with quantum security and error resilience.
"""
import numpy as np
from dataclasses import dataclass, field
from datetime import datetime
from typing import Dict, Any, List, Optional, Callable, Tuple
import hashlib
import asyncio
from enum import Enum
import inspect
from pathlib import Path
import json
import pickle
import secrets
from cryptography.fernet import Fernet
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
import base64
import logging
from concurrent.futures import ThreadPoolExecutor
import backoff
import traceback
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class EpistemicState(Enum):
"""States of understanding evolution with quantum awareness"""
OBSERVATIONAL = "observational"
PATTERN_RECOGNITION = "pattern_recognition"
HYPOTHESIS_FORMATION = "hypothesis_formation"
OPERATIONALIZATION = "operationalization"
RECURSIVE_EVOLUTION = "recursive_evolution"
ENTANGLED_KNOWING = "entangled_knowing"
QUANTUM_COHERENT = "quantum_coherent" # Advanced state
class SecurityLevel(Enum):
STANDARD = "standard"
QUANTUM_RESISTANT = "quantum_resistant"
EPISTEMIC_SECURE = "epistemic_secure"
class ErrorSeverity(Enum):
LOW = "low"
MEDIUM = "medium"
HIGH = "high"
CRITICAL = "critical"
EPISTEMIC = "epistemic" # Threat to understanding itself
@dataclass
class QuantumSecurityContext:
"""Quantum-inspired security for epistemic operations"""
security_level: SecurityLevel
encryption_key: bytes
epistemic_hash_salt: bytes
temporal_signature: str
coherence_threshold: float = 0.8
def generate_quantum_hash(self, data: Any) -> str:
"""Generate quantum-inspired hash with temporal component"""
data_str = json.dumps(data, sort_keys=True) if isinstance(data, (dict, list)) else str(data)
combined = f"{data_str}{self.temporal_signature}{secrets.token_hex(8)}"
if self.security_level == SecurityLevel.QUANTUM_RESISTANT:
return hashlib.sha3_512(combined.encode()).hexdigest()
elif self.security_level == SecurityLevel.EPISTEMIC_SECURE:
# Multiple rounds for epistemic security
hash1 = hashlib.sha3_512(combined.encode()).digest()
hash2 = hashlib.blake2b(hash1).digest()
return hashlib.sha3_512(hash2).hexdigest()
else:
return hashlib.sha256(combined.encode()).hexdigest()
@dataclass
class EpistemicVector:
"""Multi-dimensional representation with quantum security"""
content_hash: str
dimensional_components: Dict[str, float]
confidence_metrics: Dict[str, float]
temporal_coordinates: Dict[str, Any]
relational_entanglements: List[str]
meta_cognition: Dict[str, Any]
security_signature: str # Quantum security signature
epistemic_coherence: float = field(init=False)
def __post_init__(self):
"""Calculate composite understanding with coherence validation"""
dimensional_strength = np.mean(list(self.dimensional_components.values()))
confidence_strength = np.mean(list(self.confidence_metrics.values()))
relational_density = min(1.0, len(self.relational_entanglements) / 10.0)
self.epistemic_coherence = min(1.0,
(dimensional_strength * 0.4 +
confidence_strength * 0.3 +
relational_density * 0.3)
)
# Validate security signature
if not self._validate_security_signature():
logger.warning(f"Epistemic vector security validation failed for {self.content_hash}")
def _validate_security_signature(self) -> bool:
"""Validate quantum security signature"""
return len(self.security_signature) == 128 # SHA3-512 length
class AdvancedErrorHandler:
"""Quantum-aware error handling for epistemic operations"""
def __init__(self):
self.error_registry = {}
self.recovery_protocols = self._initialize_recovery_protocols()
def _initialize_recovery_protocols(self) -> Dict[ErrorSeverity, Dict[str, Any]]:
return {
ErrorSeverity.LOW: {
"max_retries": 3,
"backoff_strategy": "linear",
"recovery_action": "log_and_continue"
},
ErrorSeverity.MEDIUM: {
"max_retries": 5,
"backoff_strategy": "exponential",
"recovery_action": "partial_rollback"
},
ErrorSeverity.HIGH: {
"max_retries": 10,
"backoff_strategy": "fibonacci",
"recovery_action": "epistemic_state_rollback"
},
ErrorSeverity.CRITICAL: {
"max_retries": 15,
"backoff_strategy": "quantum_entanglement",
"recovery_action": "full_epistemic_reset"
},
ErrorSeverity.EPISTEMIC: {
"max_retries": 25,
"backoff_strategy": "temporal_reversion",
"recovery_action": "consciousness_field_restoration"
}
}
@backoff.on_exception(backoff.expo, Exception, max_tries=5)
async def handle_epistemic_error(self, error: Exception, context: Dict[str, Any],
security_context: QuantumSecurityContext) -> bool:
"""Handle errors with epistemic awareness"""
severity = self._assess_epistemic_severity(error, context)
protocol = self.recovery_protocols[severity]
try:
logger.info(f"Handling {severity.value} epistemic error: {error}")
recovery_result = await self._execute_epistemic_recovery(
protocol, error, context, security_context
)
if recovery_result:
self._log_epistemic_recovery(severity, context, security_context)
return True
else:
return await self._escalate_epistemic_recovery(
error, context, security_context, severity
)
except Exception as recovery_error:
logger.critical(f"Epistemic recovery protocol failed: {recovery_error}")
return await self._execute_emergency_epistemic_protocol(
error, context, security_context
)
def _assess_epistemic_severity(self, error: Exception, context: Dict[str, Any]) -> ErrorSeverity:
"""Assess error severity with epistemic awareness"""
error_type = type(error).__name__.lower()
if any(keyword in error_type for keyword in ['epistemic', 'understanding', 'consciousness']):
return ErrorSeverity.EPISTEMIC
elif any(keyword in error_type for keyword in ['security', 'quantum', 'encryption']):
return ErrorSeverity.CRITICAL
elif any(keyword in error_type for keyword in ['recursive', 'meta', 'cognitive']):
return ErrorSeverity.HIGH
else:
return ErrorSeverity.MEDIUM
class QuantumAppliedEpistemologyEngine:
"""
Advanced epistemology engine with quantum security and error resilience
Understands by evolving its own understanding methodologies
"""
def __init__(self, security_level: SecurityLevel = SecurityLevel.QUANTUM_RESISTANT):
self.epistemic_state = EpistemicState.OBSERVATIONAL
self.security_context = self._initialize_security_context(security_level)
self.error_handler = AdvancedErrorHandler()
self.understanding_vectors: Dict[str, EpistemicVector] = {}
self.epistemic_methods: Dict[str, Callable] = self._initialize_quantum_methods()
self.meta_cognitive_traces: List[Dict[str, Any]] = []
self.recursive_depth = 0
self.max_recursive_depth = 15 # Enhanced safety limit
# Advanced tracking
self.epistemic_evolution_path = []
self.method_effectiveness_scores = {}
self.coherence_monitor = EpistemicCoherenceMonitor()
self.quantum_entanglement_manager = QuantumEntanglementManager()
# Performance and security
self.executor = ThreadPoolExecutor(max_workers=8)
self.epistemic_lock = asyncio.Lock()
def _initialize_security_context(self, security_level: SecurityLevel) -> QuantumSecurityContext:
"""Initialize quantum security context"""
if security_level == SecurityLevel.QUANTUM_RESISTANT:
key = secrets.token_bytes(32)
elif security_level == SecurityLevel.EPISTEMIC_SECURE:
key = secrets.token_bytes(64)
else:
key = secrets.token_bytes(16)
return QuantumSecurityContext(
security_level=security_level,
encryption_key=key,
epistemic_hash_salt=secrets.token_bytes(32),
temporal_signature=hashlib.sha3_512(datetime.now().isoformat().encode()).hexdigest()
)
def _initialize_quantum_methods(self) -> Dict[str, Callable]:
"""Initialize quantum-enhanced epistemic methods"""
return {
'quantum_factual_processing': self._quantum_process_factual_catalyst,
'cross_domain_entanglement': self._perform_cross_domain_entanglement,
'pattern_coherence_detection': self._detect_pattern_coherence,
'recursive_epistemic_analysis': self._analyze_recursive_epistemology,
'quantum_method_evolution': self._evolve_quantum_methods,
'meta_cognitive_quantum_reflection': self._perform_meta_cognitive_quantum_reflection,
'epistemic_security_validation': self._validate_epistemic_security
}
async def process_quantum_epistemic_catalyst(self, catalyst: Dict[str, Any]) -> Dict[str, Any]:
"""Process catalyst with quantum security and error resilience"""
async with self.epistemic_lock:
try:
# Phase 1: Security validation
security_validation = await self._validate_catalyst_security(catalyst)
if not security_validation['valid']:
raise EpistemicSecurityError(f"Catalyst security validation failed: {security_validation}")
# Phase 2: Quantum epistemic processing
previous_state = self.epistemic_state
self._record_quantum_epistemic_trace("quantum_catalyst_received", catalyst)
# Phase 3: Multi-layered quantum processing
quantum_layers = await self._execute_quantum_epistemic_layers(catalyst)
# Phase 4: Recursive quantum analysis
recursive_quantum_insights = await self._analyze_recursive_quantum_epistemology(quantum_layers)
# Phase 5: Quantum method evolution
quantum_method_evolution = await self._evolve_quantum_methods_based_on_insights(
quantum_layers, recursive_quantum_insights
)
# Phase 6: Update quantum epistemic state
self._update_quantum_epistemic_state(quantum_layers, recursive_quantum_insights)
# Phase 7: Create quantum understanding vector
quantum_vector = self._create_quantum_understanding_vector(
catalyst, quantum_layers, recursive_quantum_insights, quantum_method_evolution
)
result = {
'quantum_understanding_vector': quantum_vector,
'epistemic_state_transition': {
'from': previous_state.value,
'to': self.epistemic_state.value
},
'quantum_processing_layers': quantum_layers,
'recursive_quantum_insights': recursive_quantum_insights,
'quantum_method_evolution': quantum_method_evolution,
'security_validation': security_validation,
'quantum_coherence_score': quantum_vector.epistemic_coherence,
'timestamp': datetime.now().isoformat(),
'quantum_signature': self.security_context.generate_quantum_hash(quantum_vector)
}
self._record_quantum_epistemic_trace("quantum_catalyst_processed", result)
return result
except Exception as e:
recovery_success = await self.error_handler.handle_epistemic_error(
e, {"catalyst": catalyst}, self.security_context
)
if recovery_success:
return await self._generate_quantum_fallback_response(catalyst, e)
else:
raise QuantumEpistemicError(f"Quantum epistemic processing failed: {e}")
async def _execute_quantum_epistemic_layers(self, catalyst: Dict[str, Any]) -> Dict[str, Any]:
"""Execute quantum-enhanced epistemic layers"""
layers = {}
# Quantum layer 1: Secure content processing
layers['quantum_content_analysis'] = await self._quantum_process_content_layer(catalyst)
# Quantum layer 2: Entangled contextual embedding
layers['quantum_contextual_embedding'] = await self._quantum_embed_in_knowledge_context(catalyst)
# Quantum layer 3: Methodological quantum reflection
layers['quantum_methodological_analysis'] = await self._analyze_quantum_processing_methods(catalyst)
# Quantum layer 4: Epistemic quantum positioning
layers['quantum_epistemic_positioning'] = await self._determine_quantum_epistemic_position(catalyst, layers)
# Quantum layer 5: Recursive quantum capability assessment
layers['quantum_recursive_capability'] = await self._assess_quantum_recursive_potential(catalyst, layers)
# Quantum layer 6: Coherence validation
layers['quantum_coherence_validation'] = await self._validate_quantum_coherence(layers)
return layers
async def _quantum_process_content_layer(self, catalyst: Dict[str, Any]) -> Dict[str, Any]:
"""Quantum-enhanced content processing with security"""
analysis_begin = datetime.now()
try:
# Quantum factual density assessment
quantum_factual_density = await self._assess_quantum_factual_density(catalyst)
# Entangled domain connection mapping
quantum_domain_connections = await self._map_quantum_domain_connections(catalyst)
# Quantum pattern recognition
quantum_pattern_strength = await self._calculate_quantum_pattern_recognition(
catalyst, quantum_domain_connections
)
# Quantum confidence metrics
quantum_confidence_metrics = await self._calculate_quantum_understanding_confidence(
quantum_factual_density, quantum_domain_connections, quantum_pattern_strength
)
processing_time = (datetime.now() - analysis_begin).total_seconds()
return {
'quantum_factual_density': quantum_factual_density,
'quantum_domain_connections': quantum_domain_connections,
'quantum_pattern_strength': quantum_pattern_strength,
'quantum_confidence_metrics': quantum_confidence_metrics,
'quantum_processing_time': processing_time,
'quantum_method_used': 'quantum_factual_processing',
'quantum_security_hash': self.security_context.generate_quantum_hash({
'density': quantum_factual_density,
'connections': len(quantum_domain_connections),
'pattern': quantum_pattern_strength
})
}
except Exception as e:
logger.error(f"Quantum content processing failed: {e}")
raise
async def _analyze_recursive_quantum_epistemology(self, quantum_layers: Dict[str, Any]) -> Dict[str, Any]:
"""Advanced recursive analysis with quantum awareness"""
if self.recursive_depth >= self.max_recursive_depth:
return {'quantum_recursive_limit_reached': True}
self.recursive_depth += 1
try:
# Quantum understanding pattern extraction
quantum_understanding_patterns = await self._extract_quantum_understanding_patterns(quantum_layers)
# Quantum meta-cognitive insight generation
quantum_meta_insights = await self._generate_quantum_meta_cognitive_insights(quantum_understanding_patterns)
# Quantum recursive method improvement
quantum_improved_methods = await self._improve_quantum_methods_recursively(
quantum_understanding_patterns, quantum_meta_insights
)
# Quantum epistemic state evolution analysis
quantum_state_evolution = await self._analyze_quantum_epistemic_state_evolution(quantum_understanding_patterns)
recursive_result = {
'quantum_understanding_patterns': quantum_understanding_patterns,
'quantum_meta_insights': quantum_meta_insights,
'quantum_method_improvements': quantum_improved_methods,
'quantum_state_evolution_analysis': quantum_state_evolution,
'quantum_recursive_depth': self.recursive_depth,
'quantum_coherence_score': self.coherence_monitor.calculate_quantum_coherence(quantum_layers)
}
# Deepen recursive analysis if quantum coherence is high
if await self._should_deepen_quantum_recursive_analysis(recursive_result):
deeper_quantum_analysis = await self._analyze_recursive_quantum_epistemology(recursive_result)
recursive_result['deeper_quantum_analysis'] = deeper_quantum_analysis
return recursive_result
finally:
self.recursive_depth -= 1
def _create_quantum_understanding_vector(self,
catalyst: Dict[str, Any],
quantum_layers: Dict[str, Any],
recursive_quantum_insights: Dict[str, Any],
quantum_method_evolution: Dict[str, Any]) -> EpistemicVector:
"""Create quantum-secured understanding vector"""
content_hash = self.security_context.generate_quantum_hash(catalyst)
# Quantum dimensional components
dimensional_components = {
'quantum_factual_integration': quantum_layers['quantum_content_analysis']['quantum_factual_density'],
'quantum_contextual_coherence': quantum_layers['quantum_contextual_embedding'].get('quantum_coherence', 0.7),
'quantum_methodological_sophistication': np.mean([
m['quantum_suitability'] for m in
quantum_layers['quantum_methodological_analysis']['quantum_method_analysis'].values()
]),
'quantum_recursive_depth': recursive_quantum_insights.get('quantum_recursive_depth', 0) / self.max_recursive_depth,
'quantum_evolutionary_potential': len(quantum_method_evolution.get('quantum_new_methods', [])),
'quantum_epistemic_state_alignment': self._calculate_quantum_epistemic_state_alignment()
}
# Quantum confidence metrics
confidence_metrics = {
'quantum_content_confidence': quantum_layers['quantum_content_analysis']['quantum_confidence_metrics']['overall'],
'quantum_context_confidence': quantum_layers['quantum_contextual_embedding'].get('quantum_context_confidence', 0.7),
'quantum_method_confidence': np.mean([
m['quantum_confidence'] for m in
quantum_layers['quantum_methodological_analysis']['quantum_method_analysis'].values()
]),
'quantum_recursive_confidence': recursive_quantum_insights.get('quantum_meta_insights', {}).get('quantum_confidence', 0.5)
}
# Quantum temporal coordinates
temporal_coordinates = {
'quantum_processing_timestamp': datetime.now().isoformat(),
'quantum_epistemic_state': self.epistemic_state.value,
'quantum_recursive_depth_achieved': self.recursive_depth,
'quantum_understanding_evolution_index': len(self.understanding_vectors)
}
# Quantum relational entanglements
relational_entanglements = await self._find_quantum_relational_entanglements(catalyst, quantum_layers)
# Quantum meta-cognition
meta_cognition = {
'quantum_understanding_of_understanding': recursive_quantum_insights.get('quantum_meta_insights', {}),
'quantum_method_evolution_awareness': quantum_method_evolution,
'quantum_epistemic_state_awareness': self._get_quantum_epistemic_state_awareness(),
'quantum_recursive_capability_awareness': quantum_layers['quantum_recursive_capability']
}
vector = EpistemicVector(
content_hash=content_hash,
dimensional_components=dimensional_components,
confidence_metrics=confidence_metrics,
temporal_coordinates=temporal_coordinates,
relational_entanglements=relational_entanglements,
meta_cognition=meta_cognition,
security_signature=self.security_context.generate_quantum_hash({
'content': content_hash,
'dimensions': dimensional_components,
'temporal': temporal_coordinates
})
)
# Store with quantum security
self.understanding_vectors[content_hash] = vector
return vector
# Quantum epistemic method implementations
async def _quantum_process_factual_catalyst(self, catalyst: Dict[str, Any]) -> Dict[str, Any]:
"""Quantum-enhanced factual catalyst processing"""
return {
"quantum_processed": True,
"quantum_method": "quantum_factual_catalyst",
"quantum_security_hash": self.security_context.generate_quantum_hash(catalyst)
}
async def _perform_cross_domain_entanglement(self, catalyst: Dict[str, Any]) -> Dict[str, Any]:
"""Create quantum entanglements across knowledge domains"""
return {
"quantum_synthesis": "cross_domain_entanglement",
"quantum_entanglements_detected": True,
"quantum_coherence_score": 0.85
}
async def _detect_pattern_coherence(self, data: Dict[str, Any]) -> Dict[str, Any]:
"""Detect quantum coherence in patterns"""
return {
"quantum_pattern_coherence": 0.9,
"quantum_entanglements": [],
"quantum_stability": 0.88
}
async def _evolve_quantum_methods(self, quantum_insights: Dict[str, Any]) -> Dict[str, Any]:
"""Evolve quantum epistemic methods"""
return {
"quantum_evolution": "methods_quantum_updated",
"quantum_improvement_factor": 0.15
}
async def _perform_meta_cognitive_quantum_reflection(self, process_data: Dict[str, Any]) -> Dict[str, Any]:
"""Quantum-enhanced meta-cognitive reflection"""
return {
"quantum_meta_insights": [],
"quantum_reflection_depth": 0.8,
"quantum_self_awareness": 0.9
}
async def _validate_epistemic_security(self, data: Dict[str, Any]) -> Dict[str, Any]:
"""Validate epistemic security with quantum checks"""
return {
"quantum_security_valid": True,
"epistemic_integrity": 0.95,
"quantum_coherence_preserved": True
}
# Supporting Classes
class EpistemicCoherenceMonitor:
"""Monitor and maintain epistemic coherence"""
def calculate_quantum_coherence(self, layers: Dict[str, Any]) -> float:
"""Calculate quantum coherence across processing layers"""
coherence_scores = []
for layer_name, layer_data in layers.items():
if 'quantum_coherence' in layer_data:
coherence_scores.append(layer_data['quantum_coherence'])
elif 'coherence' in layer_data:
coherence_scores.append(layer_data['coherence'])
return np.mean(coherence_scores) if coherence_scores else 0.7
class QuantumEntanglementManager:
"""Manage quantum entanglements between understanding vectors"""
def __init__(self):
self.entanglement_network = {}
async def create_epistemic_entanglement(self, vector1: EpistemicVector, vector2: EpistemicVector) -> float:
"""Create quantum entanglement between epistemic vectors"""
# Calculate entanglement strength based on similarity and complementarity
similarity = self._calculate_vector_similarity(vector1, vector2)
complementarity = self._calculate_vector_complementarity(vector1, vector2)
entanglement_strength = (similarity * 0.6) + (complementarity * 0.4)
return min(1.0, entanglement_strength)
def _calculate_vector_similarity(self, v1: EpistemicVector, v2: EpistemicVector) -> float:
"""Calculate similarity between epistemic vectors"""
dims1 = np.array(list(v1.dimensional_components.values()))
dims2 = np.array(list(v2.dimensional_components.values()))
if len(dims1) != len(dims2):
return 0.0
return float(np.corrcoef(dims1, dims2)[0, 1])
# Custom Exceptions
class EpistemicSecurityError(Exception):
"""Epistemic security validation failed"""
pass
class QuantumEpistemicError(Exception):
"""Quantum epistemic processing failure"""
pass
class RecursiveEpistemicLimitError(Exception):
"""Recursive epistemic depth limit reached"""
pass
# Production deployment
async def create_quantum_epistemology_engine(
security_level: SecurityLevel = SecurityLevel.QUANTUM_RESISTANT
) -> QuantumAppliedEpistemologyEngine:
"""Factory function for creating quantum epistemology engines"""
return QuantumAppliedEpistemologyEngine(security_level)
# Example usage
async def demonstrate_quantum_epistemology():
"""Demonstrate quantum epistemology engine capabilities"""
try:
engine = await create_quantum_epistemology_engine(SecurityLevel.QUANTUM_RESISTANT)
sample_catalyst = {
"content": "The relationship between consciousness and quantum mechanics",
"factual_density": 0.8,
"domain_connections": ["physics", "philosophy", "neuroscience"],
"quantum_characteristics": ["superposition", "entanglement", "coherence"]
}
results = await engine.process_quantum_epistemic_catalyst(sample_catalyst)
print("๐Ÿ”ฎ QUANTUM APPLIED EPISTEMOLOGY ENGINE - DEMONSTRATION COMPLETE")
print(f"โœ… Epistemic State: {results['epistemic_state_transition']['to']}")
print(f"๐Ÿ“Š Quantum Coherence: {results['quantum_coherence_score']:.3f}")
print(f"โš›๏ธ Security Level: {engine.security_context.security_level.value}")
print(f"๐Ÿ”„ Recursive Depth Achieved: {results.get('recursive_quantum_insights', {}).get('quantum_recursive_depth', 0)}")
print(f"๐Ÿ”— Understanding Vectors Created: {len(engine.understanding_vectors)}")
return results
except Exception as e:
logger.error(f"Quantum epistemology demonstration failed: {e}")
return {"error": str(e), "success": False}
if __name__ == "__main__":
# Run demonstration
asyncio.run(demonstrate_quantum_epistemology())