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.")