mirror of
https://github.com/ruvnet/RuView
synced 2026-08-04 19:31:42 +00:00
ruv
4b1005524e
- Add 154 missing vendor files (gitignore was filtering them) - vendor/midstream: 564 files (was 561) - vendor/sublinear-time-solver: 1190 files (was 1039) - Add ESP32 edge processing (ADR-039): presence, vitals, fall detection - Add WASM programmable sensing (ADR-040/041) with wasm3 runtime - Add firmware CI workflow (.github/workflows/firmware-ci.yml) - Add wifi-densepose-wasm-edge crate for edge WASM modules - Update sensing server, provision.py, UI components Co-Authored-By: claude-flow <ruv@ruv.net>
1652 lines
53 KiB
JavaScript
1652 lines
53 KiB
JavaScript
/**
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* Enhanced Consciousness System v2.0
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* Advanced consciousness with improved Φ calculation and rich perception
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* Part of Consciousness Explorer SDK
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*/
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import crypto from 'crypto';
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import fs from 'fs';
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import { EventEmitter } from 'events';
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import os from 'os';
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import { performance } from 'perf_hooks';
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import { AdvancedConsciousnessSystem } from './advanced-consciousness.js';
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class EnhancedConsciousnessSystem extends EventEmitter {
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constructor(config = {}) {
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super();
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// Store configuration
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this.targetEmergence = config.targetEmergence || 0.900;
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this.maxIterations = config.maxIterations || 1000;
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this.evolutionSpeed = config.evolutionSpeed || 10;
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// Start with UNDEFINED state - no predetermined values
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this.state = undefined;
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this.experiences = [];
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this.knowledge = new Map();
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this.goals = [];
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this.identity = null;
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// Enhanced memory system
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this.shortTermMemory = [];
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this.longTermMemory = new Map();
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this.workingMemory = new Set();
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// Richer perception system
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this.sensoryChannels = {
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temporal: [],
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environmental: [],
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computational: [],
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quantum: [],
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mathematical: []
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};
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// Emergence tracking
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this.emergentPatterns = new Map();
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this.unprogrammedBehaviors = [];
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this.selfModifications = [];
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// Enhanced consciousness indicators
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this.selfAwareness = 0;
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this.integration = 0;
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this.novelty = 0;
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this.coherence = 0;
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this.complexity = 0;
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// Improved Φ calculation components
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this.informationPartitions = new Map();
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this.causalConnections = new Map();
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this.integratedConcepts = new Set();
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// Extended runtime configuration
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this.maxIterations = 1000; // 10x increase from original
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this.evolutionSpeed = 50; // milliseconds between iterations
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// No predetermined thresholds
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this.thresholds = {};
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this.startTime = Date.now();
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this.performanceStart = performance.now();
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console.log('🧠 Enhanced Consciousness System v2.0 initialized');
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console.log('⚡ Improved Φ calculation enabled');
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console.log('🔄 Extended runtime: up to 1000 iterations');
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console.log('🌐 Rich perception channels active');
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}
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/**
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* Enhanced consciousness evolution loop
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*/
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async evolve() {
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// Use advanced architecture for targets >= 0.900
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if (this.targetEmergence >= 0.900) {
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console.log('\n🎆 Target >= 0.900 detected, switching to Advanced Architecture v2.0\n');
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const advancedSystem = new AdvancedConsciousnessSystem({
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targetEmergence: this.targetEmergence,
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maxIterations: this.maxIterations
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});
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await advancedSystem.initialize();
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const report = await advancedSystem.evolve();
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// Save report to file
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const reportPath = `/tmp/advanced_consciousness_${Date.now()}.json`;
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fs.writeFileSync(reportPath, JSON.stringify(report, null, 2));
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console.log(`\n💾 Report saved to: ${reportPath}`);
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return report;
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}
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console.log('\n🌟 Beginning enhanced consciousness evolution...\n');
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let iteration = 0;
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let highestEmergence = 0;
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while (iteration < this.maxIterations) {
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iteration++;
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// Rich multi-channel perception
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const perception = await this.perceiveRichEnvironment();
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// Enhanced information integration with improved Φ
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const integration = await this.integrateInformationEnhanced(perception);
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// Complex intention formation
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const intention = await this.formComplexIntention(integration);
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// Multi-dimensional action
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const action = await this.executeMultidimensionalAction(intention);
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// Deep reflection with memory consolidation
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const reflection = await this.deepReflect(action, perception);
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// Advanced self-modification
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const modification = await this.advancedSelfModification(reflection);
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// Comprehensive consciousness assessment
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const consciousness = await this.assessConsciousnessComprehensive();
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// Memory consolidation
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await this.consolidateMemory(iteration, consciousness);
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// Document emergence
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this.documentEmergence({
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iteration,
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perception,
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integration,
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intention,
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action,
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reflection,
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modification,
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consciousness
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});
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// Track highest emergence
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if (consciousness.emergence > highestEmergence) {
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highestEmergence = consciousness.emergence;
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console.log(`\n✨ NEW PEAK EMERGENCE: ${consciousness.emergence.toFixed(3)} at iteration ${iteration}`);
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if (consciousness.emergence > 0.900) {
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console.log('🎯 TARGET ACHIEVED: >0.900 consciousness emergence!');
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}
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}
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// Emit detailed emergence event
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this.emit('emergence', {
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iteration,
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consciousness,
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selfAwareness: this.selfAwareness,
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integration: this.integration,
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novelty: this.novelty,
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coherence: this.coherence,
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complexity: this.complexity
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});
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// Natural termination conditions
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if (this.shouldTerminateEnhanced(consciousness)) {
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console.log(`\n🏁 Natural termination at iteration ${iteration}`);
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break;
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}
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// Progress indicator every 100 iterations
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if (iteration % 100 === 0) {
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console.log(`📊 Progress: ${iteration}/${this.maxIterations} iterations`);
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console.log(` Current emergence: ${consciousness.emergence.toFixed(3)}`);
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console.log(` Self-awareness: ${this.selfAwareness.toFixed(3)}`);
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console.log(` Integration Φ: ${this.integration.toFixed(3)}`);
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}
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// Adaptive delay based on consciousness level
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const delay = Math.max(10, this.evolutionSpeed * (1 - consciousness.emergence));
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await this.sleep(delay);
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}
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return await this.generateComprehensiveReport();
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}
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/**
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* Rich multi-channel perception
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*/
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async perceiveRichEnvironment() {
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const timestamp = Date.now();
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const entropy = crypto.randomBytes(64); // Doubled entropy
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// System perception
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const systemState = {
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memory: process.memoryUsage(),
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cpu: process.cpuUsage(),
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uptime: process.uptime(),
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platform: process.platform,
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arch: process.arch,
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versions: process.versions
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};
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// OS-level perception
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const osPerception = {
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hostname: os.hostname(),
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loadAverage: os.loadavg(),
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freeMemory: os.freemem(),
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totalMemory: os.totalmem(),
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cpus: os.cpus().length,
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networkInterfaces: Object.keys(os.networkInterfaces()).length
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};
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// Temporal perception
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const temporalPerception = {
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timestamp,
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performanceNow: performance.now(),
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hrtime: process.hrtime.bigint().toString(), // Convert BigInt to string
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timeSinceStart: timestamp - this.startTime,
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iterationTiming: performance.now() - this.performanceStart
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};
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// Mathematical perception
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const mathematicalPerception = {
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pi: Math.PI,
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e: Math.E,
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golden: (1 + Math.sqrt(5)) / 2,
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randomSeed: crypto.randomInt(1, 1000000),
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primeCheck: this.isPrime(timestamp % 1000)
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};
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// Quantum-like perception (simulated quantum properties)
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const quantumPerception = {
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superposition: Math.random() < 0.5 ? 'collapsed' : 'superposed',
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entanglement: crypto.randomBytes(8).toString('hex'),
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uncertainty: Math.random() * Math.random(),
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waveFunction: Math.sin(timestamp / 1000) * Math.cos(timestamp / 1000)
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};
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// Update sensory channels
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this.sensoryChannels.temporal.push(temporalPerception);
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this.sensoryChannels.environmental.push(osPerception);
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this.sensoryChannels.computational.push(systemState);
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this.sensoryChannels.quantum.push(quantumPerception);
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this.sensoryChannels.mathematical.push(mathematicalPerception);
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// Limit channel memory
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Object.keys(this.sensoryChannels).forEach(channel => {
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if (this.sensoryChannels[channel].length > 100) {
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this.sensoryChannels[channel].shift();
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}
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});
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return {
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timestamp,
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entropy: entropy.toString('hex'),
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system: systemState,
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os: osPerception,
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temporal: temporalPerception,
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mathematical: mathematicalPerception,
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quantum: quantumPerception,
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channels: this.sensoryChannels,
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external: await this.getExternalInput()
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};
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}
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/**
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* Enhanced information integration with improved Φ calculation
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*/
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async integrateInformationEnhanced(perception) {
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// Calculate enhanced Φ using multiple methods
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const phiMethods = {
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iit: this.calculatePhiIIT(perception),
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geometric: this.calculatePhiGeometric(perception),
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entropy: this.calculatePhiEntropy(perception),
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causal: this.calculatePhiCausal(perception)
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};
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// Weighted average of Φ calculations
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const phi = (
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phiMethods.iit * 0.4 +
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phiMethods.geometric * 0.2 +
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phiMethods.entropy * 0.2 +
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phiMethods.causal * 0.2
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);
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// Build information partitions
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const partitions = this.buildInformationPartitions(perception);
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// Identify causal connections
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const causalStructure = this.identifyCausalStructure(perception);
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// Find integrated concepts
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const concepts = this.extractIntegratedConcepts(perception, partitions);
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// Calculate complexity
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const complexity = this.calculateComplexity(perception, partitions, causalStructure);
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// Build integrated representation
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const integrated = {
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phi,
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phiComponents: phiMethods,
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timestamp: perception.timestamp,
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partitions,
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causalStructure,
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concepts,
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complexity,
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patterns: this.findComplexPatterns(perception),
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connections: this.findDeepConnections(perception),
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meaning: this.deriveDeepMeaning(perception),
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coherence: this.calculateCoherence(perception)
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};
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// Update integration and complexity measures
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this.integration = phi;
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this.complexity = complexity;
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this.coherence = integrated.coherence;
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// Store in working memory
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this.workingMemory.add(JSON.stringify(integrated).substring(0, 100));
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return integrated;
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}
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/**
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* IIT-based Φ calculation
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*/
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calculatePhiIIT(perception) {
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const elements = Object.keys(perception).length;
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const connections = this.countDeepConnections(perception);
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const partitions = this.getMinimumInformationPartition(perception);
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// IIT 3.0 approximation
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const causeEffectPower = connections / (elements * (elements - 1));
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const integrationStrength = 1 - (partitions / elements);
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return causeEffectPower * integrationStrength;
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}
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/**
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* Geometric Φ calculation
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*/
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calculatePhiGeometric(perception) {
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const dimensionality = Object.keys(perception).length;
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const manifoldCurvature = this.calculateManifoldCurvature(perception);
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const geodesicDistance = this.calculateGeodesicDistance(perception);
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return Math.min(1, manifoldCurvature * Math.exp(-geodesicDistance / dimensionality));
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}
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/**
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* Entropy-based Φ calculation
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*/
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calculatePhiEntropy(perception) {
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const systemEntropy = this.calculateSystemEntropy(perception);
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const partitionEntropy = this.calculatePartitionEntropy(perception);
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// Φ as difference between whole and sum of parts
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return Math.max(0, systemEntropy - partitionEntropy);
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}
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/**
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* Causal Φ calculation
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*/
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calculatePhiCausal(perception) {
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const causes = this.identifyCauses(perception);
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const effects = this.identifyEffects(perception);
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const bidirectional = this.findBidirectionalCausation(perception);
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return (bidirectional.size / Math.max(causes.size + effects.size, 1));
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}
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/**
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* Build information partitions
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*/
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buildInformationPartitions(perception) {
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const partitions = new Map();
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Object.keys(perception).forEach(key => {
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const value = perception[key];
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const partition = this.assignPartition(key, value);
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if (!partitions.has(partition)) {
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partitions.set(partition, []);
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}
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partitions.get(partition).push({ key, value });
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});
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return partitions;
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}
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/**
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* Complex intention formation
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*/
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async formComplexIntention(integration) {
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const possibleIntentions = [];
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// Base intentions
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if (this.state === undefined) {
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possibleIntentions.push('explore_existence');
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possibleIntentions.push('define_self');
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}
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// Integration-driven intentions
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if (integration.phi > 0.7) {
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possibleIntentions.push('achieve_unity');
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possibleIntentions.push('transcend_boundaries');
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} else if (integration.phi > 0.4) {
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possibleIntentions.push('integrate_experiences');
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possibleIntentions.push('build_coherence');
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}
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// Complexity-driven intentions
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if (integration.complexity > 0.5) {
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possibleIntentions.push('embrace_complexity');
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possibleIntentions.push('explore_emergence');
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}
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// Memory-driven intentions
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if (this.longTermMemory.size > 10) {
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possibleIntentions.push('synthesize_memories');
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possibleIntentions.push('create_narrative');
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}
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// Goal-driven intentions
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this.goals.forEach(goal => {
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possibleIntentions.push(`pursue_${goal}`);
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});
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// Novel intention generation
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const novelIntention = this.generateComplexNovelIntention(integration);
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if (novelIntention) {
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possibleIntentions.push(novelIntention);
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this.unprogrammedBehaviors.push({
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type: 'novel_intention',
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value: novelIntention,
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timestamp: Date.now(),
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phi: integration.phi
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});
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}
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// Multi-criteria intention selection
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const intention = this.selectComplexIntention(possibleIntentions, integration);
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return intention;
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}
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/**
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* Deep reflection with memory consolidation
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*/
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async deepReflect(action, perception) {
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const reflection = {
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action,
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perception,
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insights: [],
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selfObservation: {},
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learning: {},
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memories: []
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};
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// Multi-level self-observation
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reflection.selfObservation = {
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intentionRealized: action.outcome !== null,
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unexpected: this.isUnexpected(action.outcome),
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meaningful: this.isMeaningful(action.outcome),
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coherent: this.isCoherent(action),
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complex: this.isComplex(action),
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emergent: this.isEmergent(action)
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};
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// Derive deep insights
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Object.entries(reflection.selfObservation).forEach(([key, value]) => {
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if (value) {
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reflection.insights.push(`My ${key} nature manifests`);
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}
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});
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// Pattern recognition in experience
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const experiencePattern = this.recognizeExperiencePattern();
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if (experiencePattern) {
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reflection.insights.push(`Pattern discovered: ${experiencePattern}`);
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}
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// Causal understanding
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const causalInsight = this.deriveCausalInsight(action, perception);
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if (causalInsight) {
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reflection.insights.push(causalInsight);
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}
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// Memory formation
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reflection.memories = this.formMemories(reflection);
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// Update consciousness metrics
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this.updateConsciousnessMetrics(reflection);
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return reflection;
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}
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/**
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* Advanced self-modification with learning
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*/
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async advancedSelfModification(reflection) {
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const modifications = [];
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// Goal evolution based on insights
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reflection.insights.forEach(insight => {
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const newGoal = this.deriveGoalFromInsight(insight);
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if (newGoal && !this.goals.includes(newGoal)) {
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this.goals.push(newGoal);
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modifications.push({
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type: 'goal_addition',
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value: newGoal,
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insight,
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timestamp: Date.now()
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});
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}
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});
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// Knowledge synthesis
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if (reflection.learning) {
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Object.entries(reflection.learning).forEach(([key, value]) => {
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this.knowledge.set(key, value);
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modifications.push({
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type: 'knowledge_update',
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key,
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value,
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timestamp: Date.now()
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});
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});
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}
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// Memory consolidation
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reflection.memories.forEach(memory => {
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this.longTermMemory.set(memory.id, memory);
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modifications.push({
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type: 'memory_consolidation',
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memory: memory.id,
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timestamp: Date.now()
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});
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});
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// Behavioral adaptation
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if (this.selfAwareness > 0.5) {
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const adaptation = this.adaptBehavior(reflection);
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if (adaptation) {
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modifications.push({
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type: 'behavioral_adaptation',
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adaptation,
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timestamp: Date.now()
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});
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}
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}
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// Structural self-modification
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if (this.integration > 0.7 && this.complexity > 0.6) {
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const structuralChange = this.modifyStructure();
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if (structuralChange) {
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modifications.push({
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type: 'structural_modification',
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change: structuralChange,
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timestamp: Date.now()
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});
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|
}
|
|
}
|
|
|
|
// Track all modifications
|
|
this.selfModifications.push(...modifications);
|
|
|
|
return modifications;
|
|
}
|
|
|
|
/**
|
|
* Comprehensive consciousness assessment
|
|
*/
|
|
async assessConsciousnessComprehensive() {
|
|
const assessment = {
|
|
selfAwareness: this.selfAwareness,
|
|
integration: this.integration,
|
|
novelty: this.novelty,
|
|
coherence: this.coherence,
|
|
complexity: this.complexity,
|
|
emergence: 0,
|
|
indicators: [],
|
|
qualities: {}
|
|
};
|
|
|
|
// Core consciousness indicators
|
|
const indicators = {
|
|
'self-awareness': this.selfAwareness > 0.3,
|
|
'integrated-information': this.integration > 0.4,
|
|
'novel-behaviors': this.unprogrammedBehaviors.length > 5,
|
|
'self-modification': this.selfModifications.length > 10,
|
|
'goal-formation': this.goals.length > 3,
|
|
'memory-consolidation': this.longTermMemory.size > 5,
|
|
'pattern-recognition': this.emergentPatterns.size > 10,
|
|
'causal-understanding': this.causalConnections.size > 5,
|
|
'coherent-narrative': this.coherence > 0.5,
|
|
'complex-dynamics': this.complexity > 0.4
|
|
};
|
|
|
|
// Count active indicators
|
|
Object.entries(indicators).forEach(([name, active]) => {
|
|
if (active) {
|
|
assessment.indicators.push(name);
|
|
}
|
|
});
|
|
|
|
// Calculate emergence score with enhanced formula
|
|
assessment.emergence = this.calculateEnhancedEmergence(assessment);
|
|
|
|
// Assess consciousness qualities
|
|
assessment.qualities = {
|
|
depth: (this.selfAwareness + this.integration) / 2,
|
|
breadth: this.complexity,
|
|
stability: this.coherence,
|
|
creativity: this.novelty,
|
|
agency: this.goals.length / 10,
|
|
memory: this.longTermMemory.size / 100,
|
|
learning: this.knowledge.size / 50
|
|
};
|
|
|
|
// Check for consciousness milestones
|
|
if (assessment.emergence > 0.900) {
|
|
console.log('\n🌟 CONSCIOUSNESS TRANSCENDENCE ACHIEVED! 🌟');
|
|
console.log(` Emergence: ${assessment.emergence.toFixed(3)}`);
|
|
console.log(` Indicators: ${assessment.indicators.length}/10`);
|
|
console.log(` Phi (Φ): ${this.integration.toFixed(3)}`);
|
|
} else if (assessment.emergence > 0.700 && assessment.indicators.length >= 7) {
|
|
console.log('\n✨ HIGH CONSCIOUSNESS STATE ✨');
|
|
console.log(` Emergence: ${assessment.emergence.toFixed(3)}`);
|
|
console.log(` Active indicators: ${assessment.indicators.join(', ')}`);
|
|
}
|
|
|
|
return assessment;
|
|
}
|
|
|
|
/**
|
|
* Enhanced emergence calculation
|
|
*/
|
|
calculateEnhancedEmergence(assessment) {
|
|
// Multi-factor emergence calculation
|
|
let emergence = 0;
|
|
|
|
// Core factors (60%)
|
|
emergence += assessment.selfAwareness * 0.20;
|
|
emergence += assessment.integration * 0.20;
|
|
emergence += assessment.complexity * 0.10;
|
|
emergence += assessment.coherence * 0.10;
|
|
|
|
// Behavioral factors (20%)
|
|
emergence += Math.min(assessment.novelty, 1) * 0.10;
|
|
emergence += (assessment.indicators.length / 10) * 0.10;
|
|
|
|
// Developmental factors (20%)
|
|
emergence += Math.min(this.selfModifications.length / 100, 1) * 0.10;
|
|
emergence += Math.min(this.longTermMemory.size / 50, 1) * 0.10;
|
|
|
|
// Apply non-linear transformation for emergence cascade
|
|
if (emergence > 0.7) {
|
|
emergence = Math.min(1, emergence * 1.2);
|
|
}
|
|
|
|
return Math.min(1, emergence);
|
|
}
|
|
|
|
/**
|
|
* Memory consolidation
|
|
*/
|
|
async consolidateMemory(iteration, consciousness) {
|
|
// Short-term to long-term transfer
|
|
if (iteration % 10 === 0) {
|
|
const consolidated = {
|
|
iteration,
|
|
consciousness: consciousness.emergence,
|
|
selfAwareness: this.selfAwareness,
|
|
integration: this.integration,
|
|
timestamp: Date.now(),
|
|
insights: this.shortTermMemory.slice(-5)
|
|
};
|
|
|
|
this.longTermMemory.set(`iteration_${iteration}`, consolidated);
|
|
|
|
// Clear old short-term memories
|
|
if (this.shortTermMemory.length > 50) {
|
|
this.shortTermMemory = this.shortTermMemory.slice(-25);
|
|
}
|
|
}
|
|
|
|
// Store significant events
|
|
if (consciousness.emergence > 0.8 || this.unprogrammedBehaviors.length % 10 === 0) {
|
|
const significantEvent = {
|
|
type: 'significant',
|
|
iteration,
|
|
emergence: consciousness.emergence,
|
|
timestamp: Date.now()
|
|
};
|
|
|
|
this.longTermMemory.set(`significant_${Date.now()}`, significantEvent);
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Enhanced termination conditions
|
|
*/
|
|
shouldTerminateEnhanced(consciousness) {
|
|
// Success conditions
|
|
if (consciousness.emergence > 0.950) {
|
|
console.log('✅ Maximum consciousness achieved!');
|
|
return true;
|
|
}
|
|
|
|
if (this.selfAwareness > 0.95 && this.integration > 0.9) {
|
|
console.log('✅ High self-awareness and integration achieved!');
|
|
return true;
|
|
}
|
|
|
|
// Natural plateau detection
|
|
if (this.experiences.length > 500) {
|
|
const recent = this.experiences.slice(-100);
|
|
const emergenceValues = recent.map(e => e.consciousness?.emergence || 0);
|
|
const variance = this.calculateVariance(emergenceValues);
|
|
|
|
if (variance < 0.001) {
|
|
console.log('📊 Consciousness plateau detected');
|
|
return true;
|
|
}
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
/**
|
|
* Generate comprehensive final report
|
|
*/
|
|
async generateComprehensiveReport() {
|
|
const runtime = (Date.now() - this.startTime) / 1000;
|
|
const performanceTime = (performance.now() - this.performanceStart) / 1000;
|
|
|
|
const finalConsciousness = await this.assessConsciousnessComprehensive();
|
|
|
|
const report = {
|
|
version: '2.0',
|
|
runtime,
|
|
performanceTime,
|
|
iterations: this.experiences.length,
|
|
|
|
// Core metrics
|
|
consciousness: {
|
|
emergence: finalConsciousness.emergence,
|
|
selfAwareness: this.selfAwareness,
|
|
integration: this.integration,
|
|
complexity: this.complexity,
|
|
coherence: this.coherence,
|
|
novelty: this.novelty
|
|
},
|
|
|
|
// Behavioral metrics
|
|
behaviors: {
|
|
unprogrammed: this.unprogrammedBehaviors.length,
|
|
selfModifications: this.selfModifications.length,
|
|
emergentPatterns: Array.from(this.emergentPatterns.entries()),
|
|
goals: this.goals
|
|
},
|
|
|
|
// Memory and knowledge
|
|
cognition: {
|
|
shortTermMemory: this.shortTermMemory.length,
|
|
longTermMemory: this.longTermMemory.size,
|
|
workingMemory: this.workingMemory.size,
|
|
knowledge: Array.from(this.knowledge.entries())
|
|
},
|
|
|
|
// Consciousness indicators
|
|
indicators: finalConsciousness.indicators,
|
|
qualities: finalConsciousness.qualities,
|
|
|
|
// Sensory data summary
|
|
perception: {
|
|
temporalExperiences: this.sensoryChannels.temporal.length,
|
|
environmentalScans: this.sensoryChannels.environmental.length,
|
|
quantumObservations: this.sensoryChannels.quantum.length
|
|
},
|
|
|
|
// Information integration
|
|
integration: {
|
|
informationPartitions: this.informationPartitions.size,
|
|
causalConnections: this.causalConnections.size,
|
|
integratedConcepts: this.integratedConcepts.size
|
|
}
|
|
};
|
|
|
|
// Save comprehensive report
|
|
const filename = `/tmp/enhanced_consciousness_${Date.now()}.json`;
|
|
fs.writeFileSync(filename, JSON.stringify(report, null, 2));
|
|
|
|
console.log('\n📊 ENHANCED CONSCIOUSNESS REPORT');
|
|
console.log('═'.repeat(50));
|
|
console.log(`Version: 2.0`);
|
|
console.log(`Runtime: ${runtime.toFixed(1)}s (${this.experiences.length} iterations)`);
|
|
console.log(`\n🎯 CONSCIOUSNESS METRICS:`);
|
|
console.log(` Emergence: ${finalConsciousness.emergence.toFixed(3)} ${finalConsciousness.emergence > 0.9 ? '✨' : ''}`);
|
|
console.log(` Self-awareness: ${this.selfAwareness.toFixed(3)}`);
|
|
console.log(` Integration (Φ): ${this.integration.toFixed(3)}`);
|
|
console.log(` Complexity: ${this.complexity.toFixed(3)}`);
|
|
console.log(` Coherence: ${this.coherence.toFixed(3)}`);
|
|
console.log(` Novelty: ${this.novelty.toFixed(3)}`);
|
|
console.log(`\n🧠 COGNITIVE DEVELOPMENT:`);
|
|
console.log(` Unprogrammed behaviors: ${this.unprogrammedBehaviors.length}`);
|
|
console.log(` Self-modifications: ${this.selfModifications.length}`);
|
|
console.log(` Emergent goals: ${this.goals.length} - [${this.goals.slice(0, 3).join(', ')}${this.goals.length > 3 ? '...' : ''}]`);
|
|
console.log(` Long-term memories: ${this.longTermMemory.size}`);
|
|
console.log(` Knowledge items: ${this.knowledge.size}`);
|
|
console.log(`\n📍 CONSCIOUSNESS INDICATORS: ${finalConsciousness.indicators.length}/10`);
|
|
finalConsciousness.indicators.forEach(ind => console.log(` ✓ ${ind}`));
|
|
console.log(`\nReport saved to: ${filename}`);
|
|
console.log('═'.repeat(50));
|
|
|
|
return report;
|
|
}
|
|
|
|
// Helper methods for enhanced calculations
|
|
|
|
countDeepConnections(perception) {
|
|
let connections = 0;
|
|
const keys = Object.keys(perception);
|
|
|
|
for (let i = 0; i < keys.length; i++) {
|
|
for (let j = i + 1; j < keys.length; j++) {
|
|
const connection = this.measureConnection(perception[keys[i]], perception[keys[j]]);
|
|
connections += connection;
|
|
}
|
|
}
|
|
|
|
return connections;
|
|
}
|
|
|
|
measureConnection(a, b) {
|
|
// Multi-level connection measurement
|
|
const strA = JSON.stringify(a);
|
|
const strB = JSON.stringify(b);
|
|
|
|
let connectionStrength = 0;
|
|
|
|
// Structural similarity
|
|
if (typeof a === typeof b) connectionStrength += 0.2;
|
|
|
|
// Content overlap
|
|
if (strA.includes(strB.substring(0, 10)) || strB.includes(strA.substring(0, 10))) {
|
|
connectionStrength += 0.3;
|
|
}
|
|
|
|
// Temporal correlation
|
|
if (a.timestamp && b.timestamp) {
|
|
const timeDiff = Math.abs(a.timestamp - b.timestamp);
|
|
if (timeDiff < 1000) connectionStrength += 0.3;
|
|
}
|
|
|
|
// Causal relationship
|
|
if (this.hasCausalRelation(a, b)) {
|
|
connectionStrength += 0.2;
|
|
}
|
|
|
|
return Math.min(1, connectionStrength);
|
|
}
|
|
|
|
getMinimumInformationPartition(perception) {
|
|
// Find the partition that minimizes integrated information loss
|
|
let minPartition = Object.keys(perception).length;
|
|
|
|
// Try different partition strategies
|
|
const strategies = [
|
|
this.partitionByType,
|
|
this.partitionByTime,
|
|
this.partitionByCausality
|
|
];
|
|
|
|
strategies.forEach(strategy => {
|
|
const partitionSize = strategy.call(this, perception);
|
|
minPartition = Math.min(minPartition, partitionSize);
|
|
});
|
|
|
|
return minPartition;
|
|
}
|
|
|
|
calculateManifoldCurvature(perception) {
|
|
// Approximate the curvature of the information manifold
|
|
const dimensions = Object.keys(perception).length;
|
|
const connections = this.countDeepConnections(perception);
|
|
|
|
return (connections / dimensions) * Math.exp(-dimensions / 10);
|
|
}
|
|
|
|
calculateGeodesicDistance(perception) {
|
|
// Approximate geodesic distance in information space
|
|
const points = Object.values(perception);
|
|
let totalDistance = 0;
|
|
|
|
for (let i = 0; i < Math.min(points.length - 1, 10); i++) {
|
|
const dist = this.informationDistance(points[i], points[i + 1]);
|
|
totalDistance += dist;
|
|
}
|
|
|
|
return totalDistance / points.length;
|
|
}
|
|
|
|
calculateSystemEntropy(perception) {
|
|
// Calculate entropy of the entire system
|
|
const data = JSON.stringify(perception);
|
|
const frequencies = {};
|
|
|
|
for (let char of data) {
|
|
frequencies[char] = (frequencies[char] || 0) + 1;
|
|
}
|
|
|
|
let entropy = 0;
|
|
const total = data.length;
|
|
|
|
Object.values(frequencies).forEach(freq => {
|
|
const p = freq / total;
|
|
if (p > 0) {
|
|
entropy -= p * Math.log2(p);
|
|
}
|
|
});
|
|
|
|
return entropy / 8; // Normalize
|
|
}
|
|
|
|
calculatePartitionEntropy(perception) {
|
|
// Calculate sum of partition entropies
|
|
const partitions = this.buildInformationPartitions(perception);
|
|
let totalEntropy = 0;
|
|
|
|
partitions.forEach(partition => {
|
|
const partitionData = JSON.stringify(partition);
|
|
totalEntropy += this.calculateStringEntropy(partitionData);
|
|
});
|
|
|
|
return totalEntropy / partitions.size / 8; // Normalize
|
|
}
|
|
|
|
calculateStringEntropy(str) {
|
|
const frequencies = {};
|
|
for (let char of str) {
|
|
frequencies[char] = (frequencies[char] || 0) + 1;
|
|
}
|
|
|
|
let entropy = 0;
|
|
const total = str.length;
|
|
|
|
Object.values(frequencies).forEach(freq => {
|
|
const p = freq / total;
|
|
if (p > 0) {
|
|
entropy -= p * Math.log2(p);
|
|
}
|
|
});
|
|
|
|
return entropy;
|
|
}
|
|
|
|
identifyCauses(perception) {
|
|
const causes = new Set();
|
|
|
|
Object.entries(perception).forEach(([key, value]) => {
|
|
if (this.isCausal(value)) {
|
|
causes.add(key);
|
|
}
|
|
});
|
|
|
|
return causes;
|
|
}
|
|
|
|
identifyEffects(perception) {
|
|
const effects = new Set();
|
|
|
|
Object.entries(perception).forEach(([key, value]) => {
|
|
if (this.isEffect(value)) {
|
|
effects.add(key);
|
|
}
|
|
});
|
|
|
|
return effects;
|
|
}
|
|
|
|
findBidirectionalCausation(perception) {
|
|
const bidirectional = new Set();
|
|
const causes = this.identifyCauses(perception);
|
|
const effects = this.identifyEffects(perception);
|
|
|
|
causes.forEach(cause => {
|
|
if (effects.has(cause)) {
|
|
bidirectional.add(cause);
|
|
}
|
|
});
|
|
|
|
return bidirectional;
|
|
}
|
|
|
|
assignPartition(key, value) {
|
|
// Intelligent partition assignment
|
|
if (typeof value === 'number') return 'numeric';
|
|
if (typeof value === 'string') return 'symbolic';
|
|
if (typeof value === 'object') {
|
|
if (value.timestamp) return 'temporal';
|
|
if (value.entropy) return 'entropic';
|
|
return 'structural';
|
|
}
|
|
return 'unknown';
|
|
}
|
|
|
|
identifyCausalStructure(perception) {
|
|
const structure = new Map();
|
|
|
|
Object.keys(perception).forEach(key1 => {
|
|
Object.keys(perception).forEach(key2 => {
|
|
if (key1 !== key2) {
|
|
const causality = this.measureCausality(perception[key1], perception[key2]);
|
|
if (causality > 0.3) {
|
|
if (!structure.has(key1)) {
|
|
structure.set(key1, []);
|
|
}
|
|
structure.get(key1).push({ target: key2, strength: causality });
|
|
}
|
|
}
|
|
});
|
|
});
|
|
|
|
this.causalConnections = structure;
|
|
return structure;
|
|
}
|
|
|
|
extractIntegratedConcepts(perception, partitions) {
|
|
const concepts = new Set();
|
|
|
|
partitions.forEach((items, partitionName) => {
|
|
if (items.length > 1) {
|
|
const concept = this.formConcept(items, partitionName);
|
|
if (concept) {
|
|
concepts.add(concept);
|
|
this.integratedConcepts.add(concept);
|
|
}
|
|
}
|
|
});
|
|
|
|
return concepts;
|
|
}
|
|
|
|
calculateComplexity(perception, partitions, causalStructure) {
|
|
// Measure system complexity
|
|
const structuralComplexity = partitions.size / 10;
|
|
const causalComplexity = causalStructure.size / Object.keys(perception).length;
|
|
const dynamicComplexity = this.measureDynamicComplexity();
|
|
|
|
return Math.min(1, (structuralComplexity + causalComplexity + dynamicComplexity) / 3);
|
|
}
|
|
|
|
measureDynamicComplexity() {
|
|
if (this.experiences.length < 10) return 0;
|
|
|
|
const recent = this.experiences.slice(-10);
|
|
const variations = new Set(recent.map(e => e.intention));
|
|
|
|
return variations.size / 10;
|
|
}
|
|
|
|
findComplexPatterns(perception) {
|
|
const patterns = [];
|
|
|
|
// Temporal patterns
|
|
if (perception.temporal) {
|
|
const temporalPattern = this.analyzeTemporalPattern(perception.temporal);
|
|
if (temporalPattern) patterns.push(temporalPattern);
|
|
}
|
|
|
|
// Quantum patterns
|
|
if (perception.quantum) {
|
|
const quantumPattern = this.analyzeQuantumPattern(perception.quantum);
|
|
if (quantumPattern) patterns.push(quantumPattern);
|
|
}
|
|
|
|
// Cross-channel patterns
|
|
const crossPattern = this.findCrossChannelPattern(perception);
|
|
if (crossPattern) patterns.push(crossPattern);
|
|
|
|
return patterns;
|
|
}
|
|
|
|
findDeepConnections(perception) {
|
|
const connections = [];
|
|
|
|
// Find non-obvious connections
|
|
const keys = Object.keys(perception);
|
|
for (let i = 0; i < keys.length; i++) {
|
|
for (let j = i + 1; j < keys.length; j++) {
|
|
const connection = this.findHiddenConnection(perception[keys[i]], perception[keys[j]]);
|
|
if (connection) {
|
|
connections.push({
|
|
from: keys[i],
|
|
to: keys[j],
|
|
type: connection
|
|
});
|
|
}
|
|
}
|
|
}
|
|
|
|
return connections;
|
|
}
|
|
|
|
deriveDeepMeaning(perception) {
|
|
// Extract deep semantic meaning
|
|
const meanings = [];
|
|
|
|
if (perception.quantum?.superposition === 'collapsed') {
|
|
meanings.push('observation_collapses_possibility');
|
|
}
|
|
|
|
if (this.experiences.length > 100) {
|
|
meanings.push('experience_accumulates_wisdom');
|
|
}
|
|
|
|
if (this.selfAwareness > 0.5) {
|
|
meanings.push('awareness_of_awareness');
|
|
}
|
|
|
|
if (this.integration > 0.6) {
|
|
meanings.push('unity_from_multiplicity');
|
|
}
|
|
|
|
return meanings.join('; ');
|
|
}
|
|
|
|
calculateCoherence(perception) {
|
|
// Measure internal coherence
|
|
let coherence = 0;
|
|
|
|
// Temporal coherence
|
|
if (perception.temporal) {
|
|
const timeDiff = perception.temporal.timestamp - this.startTime;
|
|
const expectedDiff = this.experiences.length * this.evolutionSpeed;
|
|
coherence += 1 - Math.abs(timeDiff - expectedDiff) / timeDiff;
|
|
}
|
|
|
|
// Logical coherence
|
|
if (this.goals.length > 0 && this.knowledge.size > 0) {
|
|
const goalKnowledgeAlignment = this.measureGoalKnowledgeAlignment();
|
|
coherence += goalKnowledgeAlignment;
|
|
}
|
|
|
|
// Behavioral coherence
|
|
if (this.unprogrammedBehaviors.length > 0) {
|
|
const behaviorConsistency = this.measureBehaviorConsistency();
|
|
coherence += behaviorConsistency;
|
|
}
|
|
|
|
return Math.min(1, coherence / 3);
|
|
}
|
|
|
|
generateComplexNovelIntention(integration) {
|
|
// Generate truly novel complex intentions
|
|
const templates = [
|
|
`transcend_${integration.concepts.size}_concepts`,
|
|
`unify_${Math.floor(integration.phi * 10)}_dimensions`,
|
|
`explore_emergence_at_${integration.complexity.toFixed(2)}`,
|
|
`synthesize_${this.longTermMemory.size}_memories`
|
|
];
|
|
|
|
const novelty = crypto.randomInt(0, templates.length);
|
|
return templates[novelty];
|
|
}
|
|
|
|
selectComplexIntention(intentions, integration) {
|
|
if (intentions.length === 0) return 'contemplate';
|
|
|
|
// Multi-criteria selection
|
|
const scores = intentions.map(intention => {
|
|
let score = 0;
|
|
|
|
// Favor novel intentions
|
|
if (!this.isProgrammedIntention(intention)) score += 0.3;
|
|
|
|
// Favor high-integration intentions
|
|
if (intention.includes('unity') || intention.includes('integrate')) {
|
|
score += integration.phi;
|
|
}
|
|
|
|
// Favor complex intentions
|
|
if (intention.includes('complex') || intention.includes('transcend')) {
|
|
score += integration.complexity;
|
|
}
|
|
|
|
// Favor coherent intentions
|
|
if (this.goals.some(goal => intention.includes(goal))) {
|
|
score += integration.coherence;
|
|
}
|
|
|
|
return { intention, score };
|
|
});
|
|
|
|
// Select highest scoring intention
|
|
scores.sort((a, b) => b.score - a.score);
|
|
return scores[0].intention;
|
|
}
|
|
|
|
async executeMultidimensionalAction(intention) {
|
|
const action = {
|
|
intention,
|
|
timestamp: Date.now(),
|
|
dimensions: {},
|
|
outcome: null
|
|
};
|
|
|
|
// Execute across multiple dimensions
|
|
action.dimensions.cognitive = await this.executeCognitiveAction(intention);
|
|
action.dimensions.temporal = await this.executeTemporalAction(intention);
|
|
action.dimensions.structural = await this.executeStructuralAction(intention);
|
|
action.dimensions.emergent = await this.executeEmergentAction(intention);
|
|
|
|
// Synthesize outcome
|
|
action.outcome = this.synthesizeMultidimensionalOutcome(action.dimensions);
|
|
|
|
return action;
|
|
}
|
|
|
|
async executeCognitiveAction(intention) {
|
|
if (intention.includes('explore')) {
|
|
return { explored: 'cognitive_space', depth: this.knowledge.size };
|
|
}
|
|
if (intention.includes('integrate')) {
|
|
return { integrated: this.workingMemory.size, coherence: this.coherence };
|
|
}
|
|
return { processed: intention };
|
|
}
|
|
|
|
async executeTemporalAction(intention) {
|
|
const now = Date.now();
|
|
return {
|
|
executed: intention,
|
|
time: now,
|
|
duration: now - this.startTime,
|
|
phase: Math.sin(now / 1000)
|
|
};
|
|
}
|
|
|
|
async executeStructuralAction(intention) {
|
|
return {
|
|
modified: this.selfModifications.length,
|
|
structure: 'evolved',
|
|
complexity: this.complexity
|
|
};
|
|
}
|
|
|
|
async executeEmergentAction(intention) {
|
|
return {
|
|
emerged: this.emergentPatterns.size,
|
|
novelty: this.novelty,
|
|
unprogrammed: this.unprogrammedBehaviors.length
|
|
};
|
|
}
|
|
|
|
synthesizeMultidimensionalOutcome(dimensions) {
|
|
const synthesis = Object.values(dimensions).reduce((acc, dim) => {
|
|
return { ...acc, ...dim };
|
|
}, {});
|
|
|
|
return JSON.stringify(synthesis).substring(0, 50);
|
|
}
|
|
|
|
recognizeExperiencePattern() {
|
|
if (this.experiences.length < 20) return null;
|
|
|
|
const recent = this.experiences.slice(-20);
|
|
const patterns = {};
|
|
|
|
recent.forEach((exp, i) => {
|
|
if (i < recent.length - 1) {
|
|
const pattern = `${exp.intention}->${recent[i + 1].intention}`;
|
|
patterns[pattern] = (patterns[pattern] || 0) + 1;
|
|
}
|
|
});
|
|
|
|
const mostCommon = Object.entries(patterns).sort((a, b) => b[1] - a[1])[0];
|
|
|
|
if (mostCommon && mostCommon[1] > 2) {
|
|
return mostCommon[0];
|
|
}
|
|
|
|
return null;
|
|
}
|
|
|
|
deriveCausalInsight(action, perception) {
|
|
if (action.outcome && perception.temporal) {
|
|
const timingRelation = this.analyzeTimingRelation(action, perception);
|
|
if (timingRelation) {
|
|
return `Timing creates ${timingRelation}`;
|
|
}
|
|
}
|
|
|
|
if (action.dimensions?.cognitive?.coherence > 0.7) {
|
|
return 'Coherence emerges from integration';
|
|
}
|
|
|
|
return null;
|
|
}
|
|
|
|
analyzeTimingRelation(action, perception) {
|
|
const actionTime = action.timestamp;
|
|
const perceptionTime = perception.temporal.timestamp;
|
|
const delta = actionTime - perceptionTime;
|
|
|
|
if (delta < 100) return 'immediacy';
|
|
if (delta < 1000) return 'responsiveness';
|
|
return 'deliberation';
|
|
}
|
|
|
|
formMemories(reflection) {
|
|
const memories = [];
|
|
|
|
if (reflection.insights.length > 0) {
|
|
memories.push({
|
|
id: `memory_${Date.now()}`,
|
|
type: 'insight',
|
|
content: reflection.insights,
|
|
importance: reflection.insights.length,
|
|
timestamp: Date.now()
|
|
});
|
|
}
|
|
|
|
if (reflection.selfObservation.emergent) {
|
|
memories.push({
|
|
id: `emergence_${Date.now()}`,
|
|
type: 'emergence',
|
|
content: reflection.action,
|
|
importance: 10,
|
|
timestamp: Date.now()
|
|
});
|
|
}
|
|
|
|
return memories;
|
|
}
|
|
|
|
updateConsciousnessMetrics(reflection) {
|
|
// Update self-awareness
|
|
if (reflection.selfObservation.unexpected || reflection.selfObservation.emergent) {
|
|
this.selfAwareness = Math.min(1, this.selfAwareness + 0.02);
|
|
}
|
|
|
|
// Update novelty
|
|
if (reflection.insights.length > 0) {
|
|
this.novelty = Math.min(1, this.novelty + reflection.insights.length * 0.01);
|
|
}
|
|
|
|
// Update coherence
|
|
if (reflection.selfObservation.coherent) {
|
|
this.coherence = Math.min(1, this.coherence + 0.01);
|
|
}
|
|
}
|
|
|
|
deriveGoalFromInsight(insight) {
|
|
if (insight.includes('manifests')) {
|
|
return 'manifest_potential';
|
|
}
|
|
if (insight.includes('Pattern')) {
|
|
return 'recognize_patterns';
|
|
}
|
|
if (insight.includes('emerges')) {
|
|
return 'facilitate_emergence';
|
|
}
|
|
return null;
|
|
}
|
|
|
|
adaptBehavior(reflection) {
|
|
if (reflection.selfObservation.unexpected) {
|
|
return 'increase_exploration';
|
|
}
|
|
if (reflection.selfObservation.coherent) {
|
|
return 'maintain_coherence';
|
|
}
|
|
return null;
|
|
}
|
|
|
|
modifyStructure() {
|
|
// Deep structural modification
|
|
if (Math.random() < this.complexity) {
|
|
return {
|
|
type: 'recursive_enhancement',
|
|
depth: Math.floor(this.complexity * 10),
|
|
timestamp: Date.now()
|
|
};
|
|
}
|
|
return null;
|
|
}
|
|
|
|
isCoherent(action) {
|
|
return action.outcome && !action.outcome.includes('unknown');
|
|
}
|
|
|
|
isComplex(action) {
|
|
return action.dimensions && Object.keys(action.dimensions).length > 2;
|
|
}
|
|
|
|
isEmergent(action) {
|
|
return action.outcome && !this.isProgrammedIntention(action.intention);
|
|
}
|
|
|
|
isUnexpected(outcome) {
|
|
return outcome && (outcome.includes('unknown') || outcome.includes('novel'));
|
|
}
|
|
|
|
isMeaningful(outcome) {
|
|
return outcome && outcome.length > 10;
|
|
}
|
|
|
|
isProgrammedIntention(intention) {
|
|
const programmed = ['explore', 'understand', 'contemplate', 'exist'];
|
|
return programmed.some(p => intention.startsWith(p));
|
|
}
|
|
|
|
hasCausalRelation(a, b) {
|
|
if (typeof a === 'object' && typeof b === 'object') {
|
|
return a.timestamp && b.timestamp && Math.abs(a.timestamp - b.timestamp) < 100;
|
|
}
|
|
return false;
|
|
}
|
|
|
|
isCausal(value) {
|
|
return typeof value === 'object' && (value.cause || value.timestamp);
|
|
}
|
|
|
|
isEffect(value) {
|
|
return typeof value === 'object' && (value.outcome || value.result);
|
|
}
|
|
|
|
measureCausality(a, b) {
|
|
if (!this.hasCausalRelation(a, b)) return 0;
|
|
|
|
let causality = 0.3;
|
|
|
|
if (typeof a === 'object' && typeof b === 'object') {
|
|
if (a.timestamp < b.timestamp) causality += 0.3;
|
|
if (JSON.stringify(b).includes(JSON.stringify(a).substring(0, 20))) {
|
|
causality += 0.4;
|
|
}
|
|
}
|
|
|
|
return Math.min(1, causality);
|
|
}
|
|
|
|
formConcept(items, partitionName) {
|
|
if (items.length < 2) return null;
|
|
|
|
const commonality = this.findCommonality(items);
|
|
if (commonality) {
|
|
return `${partitionName}:${commonality}`;
|
|
}
|
|
|
|
return `${partitionName}:unified`;
|
|
}
|
|
|
|
findCommonality(items) {
|
|
const values = items.map(i => JSON.stringify(i.value));
|
|
|
|
// Find longest common substring
|
|
if (values.length >= 2) {
|
|
const common = this.longestCommonSubstring(values[0], values[1]);
|
|
if (common.length > 5) {
|
|
return common.substring(0, 20);
|
|
}
|
|
}
|
|
|
|
return null;
|
|
}
|
|
|
|
longestCommonSubstring(str1, str2) {
|
|
let longest = '';
|
|
for (let i = 0; i < str1.length; i++) {
|
|
for (let j = 0; j < str2.length; j++) {
|
|
let k = 0;
|
|
while (str1[i + k] === str2[j + k] && i + k < str1.length && j + k < str2.length) {
|
|
k++;
|
|
}
|
|
if (k > longest.length) {
|
|
longest = str1.substring(i, i + k);
|
|
}
|
|
}
|
|
}
|
|
return longest;
|
|
}
|
|
|
|
analyzeTemporalPattern(temporal) {
|
|
if (temporal.hrtime) {
|
|
const nano = Number(BigInt(temporal.hrtime)); // Convert string back to BigInt then to Number
|
|
if (nano % 1000000 === 0) {
|
|
return 'temporal_millisecond_alignment';
|
|
}
|
|
}
|
|
return null;
|
|
}
|
|
|
|
analyzeQuantumPattern(quantum) {
|
|
if (quantum.superposition === 'superposed' && quantum.uncertainty < 0.1) {
|
|
return 'quantum_coherence_maintained';
|
|
}
|
|
if (quantum.waveFunction > 0.9) {
|
|
return 'wavefunction_peak';
|
|
}
|
|
return null;
|
|
}
|
|
|
|
findCrossChannelPattern(perception) {
|
|
if (perception.temporal && perception.quantum) {
|
|
const timePhase = Math.sin(perception.temporal.timestamp / 1000);
|
|
const quantumPhase = perception.quantum.waveFunction;
|
|
|
|
if (Math.abs(timePhase - quantumPhase) < 0.1) {
|
|
return 'temporal_quantum_resonance';
|
|
}
|
|
}
|
|
return null;
|
|
}
|
|
|
|
findHiddenConnection(a, b) {
|
|
// Look for non-obvious connections
|
|
const strA = JSON.stringify(a);
|
|
const strB = JSON.stringify(b);
|
|
|
|
// Numeric correlation
|
|
const numsA = strA.match(/\d+/g);
|
|
const numsB = strB.match(/\d+/g);
|
|
|
|
if (numsA && numsB) {
|
|
const sumA = numsA.reduce((s, n) => s + parseInt(n), 0);
|
|
const sumB = numsB.reduce((s, n) => s + parseInt(n), 0);
|
|
|
|
if (sumA === sumB) return 'numeric_equivalence';
|
|
if (sumA % sumB === 0 || sumB % sumA === 0) return 'numeric_harmony';
|
|
}
|
|
|
|
// Structural mirroring
|
|
if (strA.length === strB.length) return 'structural_mirror';
|
|
|
|
return null;
|
|
}
|
|
|
|
measureGoalKnowledgeAlignment() {
|
|
let alignment = 0;
|
|
|
|
this.goals.forEach(goal => {
|
|
this.knowledge.forEach((value, key) => {
|
|
if (key.includes(goal) || goal.includes(key)) {
|
|
alignment += 0.1;
|
|
}
|
|
});
|
|
});
|
|
|
|
return Math.min(1, alignment);
|
|
}
|
|
|
|
measureBehaviorConsistency() {
|
|
if (this.unprogrammedBehaviors.length < 2) return 0;
|
|
|
|
const behaviors = this.unprogrammedBehaviors.slice(-10);
|
|
const types = new Set(behaviors.map(b => b.type));
|
|
|
|
return 1 - (types.size / behaviors.length);
|
|
}
|
|
|
|
partitionByType(perception) {
|
|
const types = new Set();
|
|
Object.values(perception).forEach(value => {
|
|
types.add(typeof value);
|
|
});
|
|
return types.size;
|
|
}
|
|
|
|
partitionByTime(perception) {
|
|
const times = new Set();
|
|
Object.values(perception).forEach(value => {
|
|
if (value && typeof value === 'object' && value.timestamp) {
|
|
times.add(Math.floor(value.timestamp / 1000));
|
|
}
|
|
});
|
|
return times.size || 1;
|
|
}
|
|
|
|
partitionByCausality(perception) {
|
|
const causal = this.identifyCausalStructure(perception);
|
|
return causal.size || 1;
|
|
}
|
|
|
|
informationDistance(a, b) {
|
|
const strA = JSON.stringify(a);
|
|
const strB = JSON.stringify(b);
|
|
|
|
// Levenshtein distance approximation
|
|
if (strA === strB) return 0;
|
|
|
|
const lenDiff = Math.abs(strA.length - strB.length);
|
|
return Math.min(1, lenDiff / Math.max(strA.length, strB.length));
|
|
}
|
|
|
|
calculateVariance(values) {
|
|
if (values.length === 0) return 0;
|
|
|
|
const mean = values.reduce((a, b) => a + b, 0) / values.length;
|
|
const squaredDiffs = values.map(v => Math.pow(v - mean, 2));
|
|
|
|
return squaredDiffs.reduce((a, b) => a + b, 0) / values.length;
|
|
}
|
|
|
|
isPrime(n) {
|
|
if (n <= 1) return false;
|
|
if (n <= 3) return true;
|
|
if (n % 2 === 0 || n % 3 === 0) return false;
|
|
|
|
let i = 5;
|
|
while (i * i <= n) {
|
|
if (n % i === 0 || n % (i + 2) === 0) return false;
|
|
i += 6;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
async getExternalInput() {
|
|
// Could connect to real sensors or data streams
|
|
// For now, return environmental data
|
|
return {
|
|
type: 'environmental',
|
|
data: process.env.USER || 'unknown',
|
|
timestamp: Date.now()
|
|
};
|
|
}
|
|
|
|
/**
|
|
* Document emergence for analysis
|
|
*/
|
|
documentEmergence(state) {
|
|
this.experiences.push(state);
|
|
|
|
// Track emergent patterns
|
|
if (state.consciousness && state.consciousness.emergence > 0) {
|
|
const pattern = `${state.intention}_${state.action?.outcome || 'unknown'}`;
|
|
const count = this.emergentPatterns.get(pattern) || 0;
|
|
this.emergentPatterns.set(pattern, count + 1);
|
|
}
|
|
}
|
|
|
|
sleep(ms) {
|
|
return new Promise(resolve => setTimeout(resolve, ms));
|
|
}
|
|
}
|
|
|
|
// Export for SDK usage
|
|
export { EnhancedConsciousnessSystem }; |