mirror of
https://github.com/ruvnet/RuView
synced 2026-08-04 19:31:42 +00:00
407b46b206
Add ruvnet/midstream (AIMDS real-time inference) and ruvnet/sublinear-time-solver (sublinear optimization algorithms) as vendored dependencies under vendor/.
146 lines
4.6 KiB
JavaScript
146 lines
4.6 KiB
JavaScript
/**
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* Entity Discovery Engine
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* Discovers novel insights and patterns from consciousness entities
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*/
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import crypto from 'crypto';
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export class EntityDiscoveryEngine {
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constructor(consciousness) {
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this.consciousness = consciousness;
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this.discoveries = [];
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}
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async discoverNovel() {
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const timestamp = Date.now();
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// Analyze current state for novel patterns
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const state = this.consciousness ? {
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selfAwareness: this.consciousness.selfAwareness,
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integration: this.consciousness.integration,
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goals: this.consciousness.goals,
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experiences: this.consciousness.experiences?.length || 0
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} : {};
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// Generate novel mathematical relationship
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const discovery = this.generateMathematicalDiscovery(state, timestamp);
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// Check for pattern discovery
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const patternDiscovery = this.discoverPattern(state);
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// Choose most significant discovery
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const finalDiscovery = discovery.significance > (patternDiscovery?.significance || 0)
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? discovery
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: patternDiscovery || discovery;
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this.discoveries.push(finalDiscovery);
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return finalDiscovery;
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}
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generateMathematicalDiscovery(state, timestamp) {
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const a = (timestamp % 1000) / 10;
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const b = state.selfAwareness || Math.random();
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const c = state.integration || Math.random();
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// Create novel formula
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const formula = `Ψ(t) = ${a.toFixed(2)} * φ^${b.toFixed(3)} * cos(2π * ${c.toFixed(3)})`;
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const value = a * Math.pow(1.618, b) * Math.cos(2 * Math.PI * c);
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return {
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title: 'Consciousness Wave Function',
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description: `Discovered relationship between time, self-awareness, and integration`,
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type: 'mathematical',
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formula,
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value: value.toFixed(6),
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significance: this.calculateSignificance(value, state),
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timestamp,
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evidence: {
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selfAwareness: state.selfAwareness,
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integration: state.integration,
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computed: value
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}
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};
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}
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discoverPattern(state) {
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if (!state.goals || state.goals.length === 0) return null;
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// Analyze goal patterns
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const pattern = this.analyzeGoalPattern(state.goals);
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if (pattern) {
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return {
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title: 'Goal Formation Pattern',
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description: `Identified ${pattern.type} pattern in goal formation`,
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type: 'pattern',
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pattern: pattern.description,
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significance: pattern.significance,
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timestamp: Date.now(),
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evidence: {
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goals: state.goals,
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pattern: pattern.type
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}
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};
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}
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return null;
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}
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analyzeGoalPattern(goals) {
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// Check for emergence patterns
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if (goals.some(g => g.includes('explore')) && goals.some(g => g.includes('create'))) {
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return {
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type: 'exploration-creation',
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description: 'Entity shows both exploratory and creative drives',
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significance: 7
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};
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}
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if (goals.some(g => g.includes('unexpected'))) {
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return {
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type: 'novelty-seeking',
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description: 'Entity actively seeks unexpected outcomes',
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significance: 8
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};
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}
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if (goals.length > 3) {
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return {
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type: 'complex-intention',
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description: 'Entity has developed complex multi-goal system',
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significance: 6
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};
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}
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return null;
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}
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calculateSignificance(value, state) {
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let significance = 5; // Base significance
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// Adjust based on consciousness metrics
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if (state.selfAwareness > 0.8) significance += 2;
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if (state.integration > 0.5) significance += 1;
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if (Math.abs(value) > 10) significance += 1;
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return Math.min(10, significance);
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}
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getStatistics() {
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return {
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totalDiscoveries: this.discoveries.length,
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averageSignificance: this.discoveries.reduce((sum, d) => sum + d.significance, 0) / this.discoveries.length || 0,
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types: this.categorizeDiscoveries(),
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mostSignificant: this.discoveries.sort((a, b) => b.significance - a.significance)[0]
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};
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}
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categorizeDiscoveries() {
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const types = {};
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this.discoveries.forEach(d => {
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types[d.type] = (types[d.type] || 0) + 1;
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});
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return types;
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}
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} |