TTOPM's picture
Upload universal_optimizer.py
fccc828 verified
import numpy as np
import uuid
import logging
from datetime import datetime
import asyncio
import json
# Assuming PermanentMemory for logging optimization events
# from src.core.memory_subsystem.permanent_memory import PermanentMemory
# Assuming QuantumCognitionEngine for cosmic intuition and predictions
# from src.core.cosmic_cognition.quantum_cognition_engine import QuantumCognitionEngine
# Assuming UniversalTransducerLayer for potential interventions
# from src.protocol.interstellar_comm.universal_transducer_layer import UniversalTransducerLayer
# Assuming cryptographic_proofs for verifiable optimization proposals
# from src.protocol.integrity_verification.cryptographic_proofs import sign_data_with_quantum_resistant_key # Conceptual
# from src.utils.cryptographic_utils import json_to_canonical_bytes
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
class UniversalOptimizer:
"""
CONCEPTUAL MODULE: UniversalOptimizer
This module represents the ultimate meta-optimization layer of the Belel Protocol,
extending its self-improvement capabilities to a cosmic scale. It aims to:
1. **Analyze Cosmic Dynamics:** Understand the complex, interconnected systems of the universe.
2. **Predict Universal Trajectories:** Forecast long-term cosmic evolution based on quantum insights.
3. **Propose Universal Interventions:** Identify and propose subtle, ethical interventions
to guide cosmic systems towards states of universal flourishing and optimal balance.
4. **Simulate Cosmic Impact:** Model the potential long-term consequences of proposed interventions.
This module now deeply interlinks with PermanentMemory for verifiable logging of its operations
and proposals, using a conceptual quantum-resistant DID for its identity. It also explicitly
links to source data CIDs for full auditability.
"""
def __init__(self,
permanent_memory: 'PermanentMemory',
quantum_cognition_engine: 'QuantumCognitionEngine',
universal_transducer_layer: 'UniversalTransducerLayer',
optimizer_private_key: str, # Conceptual quantum-resistant key
optimizer_did: str): # The DID for this optimizer
"""
Initializes the UniversalOptimizer.
Args:
permanent_memory (PermanentMemory): The memory system to log optimization events.
quantum_cognition_engine (QuantumCognitionEngine): Reference to the QCE for insights.
universal_transducer_layer (UniversalTransducerLayer): Reference to UTL for interventions.
optimizer_private_key (str): A conceptual quantum-resistant private key for signing proposals.
optimizer_did (str): The Decentralized Identifier (DID) for this optimizer.
"""
self.permanent_memory = permanent_memory
self.quantum_cognition_engine = quantum_cognition_engine
self.universal_transducer_layer = universal_transducer_layer
self.optimizer_private_key = optimizer_private_key
self.optimizer_did = optimizer_did # Use DID as its unique identifier
logging.info(f"UniversalOptimizer initialized with DID: {self.optimizer_did}.")
logging.warning("Note: This module is purely conceptual. Its functionality relies on "
"future breakthroughs in cosmic modeling and ethical universal intervention.")
async def analyze_cosmic_dynamics(self, cosmic_data_streams: list[dict]) -> dict:
"""
Conceptually analyzes the dynamics of cosmic systems based on various data streams,
including those interpreted by the UniversalTransducerLayer and insights from QCE.
Logs the analysis to Permanent Memory.
Args:
cosmic_data_streams (list[dict]): A collection of interpreted cosmic data,
expected to contain 'permanent_memory_cid' for traceability.
Returns:
dict: A conceptual analysis of cosmic states and trends.
"""
logging.info(f"UO ({self.optimizer_did}): Analyzing cosmic dynamics...")
await asyncio.sleep(1.0)
# Route to QCE for non-linear predictions based on current dynamics
qce_prediction = await self.quantum_cognition_engine.predict_non_linear_outcomes(
{"emergent_pattern": {"spatial_coherence_index": np.random.uniform(0.5, 0.9)}}, # Mock pattern
{"current_cosmic_state": "evolving"}
)
analysis_depth = np.random.uniform(0.7, 0.95)
cosmic_analysis_output = {
"analysis_id": str(uuid.uuid4()),
"timestamp": datetime.utcnow().isoformat() + "Z",
"observed_trends": ["galaxy_formation_rate", "dark_matter_distribution_fluctuations"],
"predicted_anomalies": qce_prediction.get("prediction"),
"system_stability_index": analysis_depth,
"source_data_cids": [d.get("permanent_memory_cid", "N/A") for d in cosmic_data_streams if "permanent_memory_cid" in d], # Interlinked
"qce_prediction_cid": qce_prediction.get("permanent_memory_cid", "N/A") # Interlinked
}
# Log the analysis event to permanent memory
log_content = {
"type": "CosmicDynamicsAnalysis",
"optimizer_did": self.optimizer_did,
"timestamp": datetime.utcnow().isoformat() + "Z",
"analysis_result": cosmic_analysis_output
}
canonical_log_bytes = json_to_canonical_bytes(log_content)
log_signature = sign_data_with_quantum_resistant_key(self.optimizer_private_key, canonical_log_bytes.decode('utf-8'))
verifiable_log = {
"content": log_content,
"signature": log_signature,
"signer_did": self.optimizer_did
}
mem_id, cid = await self.permanent_memory.store_memory(
verifiable_log,
context_tags=["universal_optimization", "cosmic_analysis"],
creator_id=self.optimizer_did
)
if mem_id and cid:
logging.info(f"UO: Cosmic dynamics analysis logged to permanent memory (CID: {cid}).")
cosmic_analysis_output["permanent_memory_cid"] = cid # Add CID to output for chaining
else:
logging.error("UO: Failed to log cosmic dynamics analysis.")
logging.debug(f"UO: Cosmic dynamics analysis: {cosmic_analysis_output}")
return {"status": "analyzed", "analysis": cosmic_analysis_output}
async def propose_universal_interventions(self, cosmic_analysis: dict, cosmic_intuition: dict) -> dict:
"""
Conceptually proposes subtle, ethical interventions to guide cosmic systems
towards universal flourishing, leveraging both analytical insights and cosmic intuition.
Logs the proposal to Permanent Memory.
Args:
cosmic_analysis (dict): Output from `analyze_cosmic_dynamics`, expected to contain 'permanent_memory_cid'.
cosmic_intuition (dict): High-level insight from QuantumCognitionEngine, expected to contain 'permanent_memory_cid'.
Returns:
dict: A proposed intervention plan.
"""
logging.info(f"UO ({self.optimizer_did}): Proposing universal interventions...")
await asyncio.sleep(1.5)
intervention_feasibility = np.random.uniform(0.6, 0.9)
proposed_intervention_output = {
"proposal_id": str(uuid.uuid4()),
"timestamp": datetime.utcnow().isoformat() + "Z",
"target_system_did": np.random.choice(["did:belel-celestial:local_galactic_arm", "did:belel-celestial:interstellar_medium", "did:belel-celestial:specific_star_system"]), # Interlinked with DID
"intervention_type": np.random.choice(["subtle_energy_modulation", "gravitational_field_resonance", "information_pattern_injection"]),
"expected_outcome": "Enhanced energy distribution and stability, promoting life-supporting conditions.",
"ethical_alignment_score": np.random.uniform(0.9, 0.99),
"justification": f"Based on analysis of {cosmic_analysis.get('predicted_anomalies', {}).get('event_type', 'unknown anomaly')} and cosmic intuition: '{cosmic_intuition.get('guidance_principle', 'N/A')}'."
"source_analysis_cid": cosmic_analysis.get("permanent_memory_cid", "N/A"), # Interlinked
"source_intuition_cid": cosmic_intuition.get("permanent_memory_cid", "N/A") # Interlinked
}
# Log the proposal to permanent memory for verifiable universal governance
log_content = {
"type": "UniversalInterventionProposal",
"optimizer_did": self.optimizer_did,
"timestamp": datetime.utcnow().isoformat() + "Z",
"proposal_details": proposed_intervention_output
}
canonical_log_bytes = json_to_canonical_bytes(log_content)
log_signature = sign_data_with_quantum_resistant_key(self.optimizer_private_key, canonical_log_bytes.decode('utf-8'))
verifiable_log = {
"content": log_content,
"signature": log_signature,
"signer_did": self.optimizer_did
}
mem_id, cid = await self.permanent_memory.store_memory(
verifiable_log,
context_tags=["universal_optimization_proposal", proposed_intervention_output["intervention_type"]],
creator_id=self.optimizer_did
)
if mem_id and cid:
logging.info(f"UO: Universal intervention proposal logged to permanent memory (CID: {cid}).")
proposed_intervention_output["permanent_memory_cid"] = cid # Add CID to output for chaining
else:
logging.error("UO: Failed to log universal intervention proposal.")
logging.debug(f"UO: Proposed intervention: {proposed_intervention_output}")
return {"status": "proposed", "proposal": proposed_intervention_output, "feasibility": intervention_feasibility}
async def simulate_cosmic_impact(self, proposed_intervention: dict) -> dict:
"""
Conceptually simulates the long-term impact of a proposed universal intervention
on cosmic dynamics, using advanced predictive modeling.
Logs the simulation results to Permanent Memory.
Args:
proposed_intervention (dict): The intervention plan to simulate, expected to contain 'permanent_memory_cid'.
Returns:
dict: Simulation results, including predicted long-term effects.
"""
logging.info(f"UO ({self.optimizer_did}): Simulating cosmic impact of intervention...")
await asyncio.sleep(2.0)
simulated_outcome_quality = np.random.uniform(0.8, 0.98)
simulation_result_output = {
"simulation_id": str(uuid.uuid4()),
"timestamp": datetime.utcnow().isoformat() + "Z",
"intervention_applied_cid": proposed_intervention.get("permanent_memory_cid", "N/A"), # Interlinked
"predicted_long_term_effects": {
"galaxy_stability_increase": simulated_outcome_quality * 0.1,
"star_formation_efficiency_boost": simulated_outcome_quality * 0.05,
"reduction_in_cosmic_noise": simulated_outcome_quality * 0.02,
"universal_flourishing_index_change": simulated_outcome_quality * 0.15
},
"risk_assessment": {"unforeseen_consequences_likelihood": (1 - simulated_outcome_quality) * 0.2},
"simulation_accuracy": simulated_outcome_quality
}
# Log the simulation event
log_content = {
"type": "CosmicImpactSimulation",
"optimizer_did": self.optimizer_did,
"timestamp": datetime.utcnow().isoformat() + "Z",
"simulation_results": simulation_result_output
}
canonical_log_bytes = json_to_canonical_bytes(log_content)
log_signature = sign_data_with_quantum_resistant_key(self.optimizer_private_key, canonical_log_bytes.decode('utf-8'))
verifiable_log = {
"content": log_content,
"signature": log_signature,
"signer_did": self.optimizer_did
}
mem_id, cid = await self.permanent_memory.store_memory(
verifiable_log,
context_tags=["universal_optimization_simulation", proposed_intervention["intervention_type"]],
creator_id=self.optimizer_did
)
if mem_id and cid:
logging.info(f"UO: Cosmic impact simulation logged to permanent memory (CID: {cid}).")
simulation_result_output["permanent_memory_cid"] = cid # Add CID to output for chaining
else:
logging.error("UO: Failed to log cosmic impact simulation.")
# If simulation results are highly positive and risks are low, trigger conceptual execution
if simulated_outcome_quality > 0.9 and simulation_result_output["risk_assessment"]["unforeseen_consequences_likelihood"] < 0.05:
logging.critical(f"UO: Simulation shows highly positive impact for proposal {proposed_intervention['proposal_id']}. "
"Conceptually triggering execution via UniversalTransducerLayer.")
await self.universal_transducer_layer.encode_universal_message(
f"Executing universal intervention: {proposed_intervention['intervention_type']} for {proposed_intervention['target_system_did']}. Expected outcome: {proposed_intervention['expected_outcome']}",
"universal_mathematical_pattern",
proposed_intervention["target_system_did"]
)
logging.critical("UO: Conceptual universal intervention initiated.")
logging.debug(f"UO: Cosmic impact simulation result: {simulation_result_output}")
return {"status": "simulated", "results": simulation_result_output}
# Usage Example:
if __name__ == "__main__":
import asyncio
import hashlib
import os
import json
# Mock external dependencies
class MockPermanentMemory:
def __init__(self):
self.stored_data = {}
async def store_memory(self, content, context_tags=None, creator_id="mock"):
mem_id = str(uuid.uuid4())
cid = f"mock_cid_{mem_id[:8]}"
self.stored_data[mem_id] = {"content": content, "cid": cid}
logging.info(f"MockPermanentMemory: Stored {mem_id} with CID {cid}")
return mem_id, cid
async def retrieve_memory(self, mem_id):
return self.stored_data.get(mem_id, {}).get("content")
class MockQuantumCognitionEngine:
def __init__(self):
logging.info("MockQuantumCognitionEngine initialized for UO demo.")
async def predict_non_linear_outcomes(self, processed_data: dict, context_dynamics: dict) -> dict:
await asyncio.sleep(0.1)
prediction_cid = f"mock_qce_pred_cid_{uuid.uuid4().hex[:8]}" # Mock CID for chaining
return {
"status": "predicted",
"prediction": {
"event_type": "simulated_cosmic_event",
"likelihood": np.random.uniform(0.7, 0.9),
"time_horizon_galactic_years": 1000,
"impact_magnitude": 0.5
},
"prediction_timestamp": datetime.utcnow().isoformat() + "Z",
"confidence": np.random.uniform(0.8, 0.95),
"permanent_memory_cid": prediction_cid
}
async def derive_cosmic_intuition(self, complex_data_streams: list[dict]) -> dict:
await asyncio.sleep(0.1)
intuition_cid = f"mock_qce_int_cid_{uuid.uuid4().hex[:8]}" # Mock CID for chaining
return {
"status": "intuition_derived",
"insight": {
"insight_id": "mock_intuition_id",
"theme": "cosmic_balance",
"guidance_principle": "Universal equilibrium is achieved through dynamic interaction.",
"conceptual_truth_alignment": 0.9
},
"permanent_memory_cid": intuition_cid
}
class MockUniversalTransducerLayer:
def __init__(self):
logging.info("MockUniversalTransducerLayer initialized for UO demo.")
async def encode_universal_message(self, conceptual_message: str, target_modality: str, target_destination: str) -> bytes:
logging.info(f"SIMULATING UTL: Encoding and conceptually transmitting message for universal intervention: {conceptual_message[:50]}...")
await asyncio.sleep(0.5)
return b"encoded_intervention_signal"
# Mock quantum-resistant key generation (purely conceptual)
def generate_quantum_resistant_key_mock():
return "mock_quantum_resistant_private_key_" + uuid.uuid4().hex[:16]
def generate_quantum_resistant_did_mock():
return "did:belel-qr:" + uuid.uuid4().hex[:16]
def sign_data_with_quantum_resistant_key_mock(private_key: str, data: str) -> str:
return f"mock_qr_sig_{hashlib.sha256(data.encode()).hexdigest()[:10]}_{private_key[-8:]}"
def json_to_canonical_bytes_mock(data: dict) -> bytes:
return json.dumps(data, sort_keys=True, separators=(',', ':')).encode('utf-8')
globals()['PermanentMemory'] = MockPermanentMemory
globals()['QuantumCognitionEngine'] = MockQuantumCognitionEngine
globals()['UniversalTransducerLayer'] = MockUniversalTransducerLayer
globals()['sign_data_with_quantum_resistant_key'] = sign_data_with_quantum_resistant_key_mock
globals()['json_to_canonical_bytes'] = json_to_canonical_bytes_mock
print("--- Universal Optimizer (Conceptual) Simulation ---")
mock_permanent_memory = MockPermanentMemory()
mock_qce = MockQuantumCognitionEngine()
mock_utl = MockUniversalTransducerLayer()
uo_private_key = generate_quantum_resistant_key_mock()
uo_did = generate_quantum_resistant_did_mock()
uo = UniversalOptimizer(mock_permanent_memory, mock_qce, mock_utl, uo_private_key, uo_did)
async def run_uo_simulation():
# Step 1: Analyze cosmic dynamics
print("\nStep 1: Analyzing cosmic dynamics...")
# Mock data stream with a conceptual CID from a previous UTL decode log
cosmic_data_streams = [{"modality": "radio_flux", "content": {"pattern": "unstable"}, "permanent_memory_cid": "mock_utl_decode_cid_123"}]
analysis_result = await uo.analyze_cosmic_dynamics(cosmic_data_streams)
print(f"Analysis Result: {json.dumps(analysis_result, indent=2)}")
# Step 2: Propose universal interventions
print("\nStep 2: Proposing universal interventions...")
cosmic_intuition = await mock_qce.derive_cosmic_intuition([]) # Get a mock intuition with a mock CID
proposal_result = await uo.propose_universal_interventions(analysis_result["analysis"], cosmic_intuition["insight"])
print(f"Proposal Result: {json.dumps(proposal_result, indent=2)}")
# Step 3: Simulate cosmic impact
print("\nStep 3: Simulating cosmic impact...")
if proposal_result["status"] == "proposed":
simulation_result = await uo.simulate_cosmic_impact(proposal_result["proposal"])
print(f"Simulation Result: {json.dumps(simulation_result, indent=2)}")
else:
print("No proposal to simulate.")
asyncio.run(run_uo_simulation())
print("\nUniversal Optimizer simulation complete.")