98 lines
4.3 KiB
JavaScript
98 lines
4.3 KiB
JavaScript
/**
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* Psycho-Symbolic-Reasoner Integration
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*
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* Hybrid symbolic/subsymbolic graph database
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* Integration with psycho-symbolic-reasoner package
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*
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* Combines:
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* - Psychological reasoning models
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* - Symbolic logic
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* - Subsymbolic pattern recognition
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*/
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import { createUnifiedDatabase } from '../../src/db-unified.js';
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import { ReflexionMemory } from '../../src/controllers/ReflexionMemory.js';
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import { CausalMemoryGraph } from '../../src/controllers/CausalMemoryGraph.js';
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import { SkillLibrary } from '../../src/controllers/SkillLibrary.js';
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import { EmbeddingService } from '../../src/controllers/EmbeddingService.js';
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import * as path from 'path';
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export default {
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description: 'Psycho-symbolic reasoner with hybrid symbolic/subsymbolic processing',
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async run(config) {
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const { verbosity = 2 } = config;
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if (verbosity >= 2) {
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console.log(' 🧩 Initializing Psycho-Symbolic Reasoner');
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}
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// Initialize hybrid graph database
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const embedder = new EmbeddingService({
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model: 'Xenova/all-MiniLM-L6-v2',
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dimension: 384,
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provider: 'transformers'
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});
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await embedder.initialize();
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const db = await createUnifiedDatabase(path.join(process.cwd(), 'simulation', 'data', 'advanced', 'psycho-symbolic.graph'), embedder, { forceMode: 'graph' });
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const reflexion = new ReflexionMemory(db.getGraphDatabase(), embedder, undefined, undefined, db.getGraphDatabase());
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const causal = new CausalMemoryGraph(db.getGraphDatabase(), db.getGraphDatabase());
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const skills = new SkillLibrary(db.getGraphDatabase(), embedder, undefined, db.getGraphDatabase());
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const results = {
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psychologicalModels: 0,
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symbolicRules: 0,
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subsymbolicPatterns: 0,
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hybridReasoning: 0,
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totalTime: 0
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};
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const startTime = performance.now();
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// Psychological reasoning models (cognitive biases, heuristics)
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const psychModels = [
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{ model: 'confirmation_bias', strength: 0.88 },
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{ model: 'availability_heuristic', strength: 0.85 },
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{ model: 'anchoring_effect', strength: 0.90 }
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];
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for (const model of psychModels) {
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await reflexion.storeEpisode({
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sessionId: 'psycho-model',
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task: `psychological_model: ${model.model}`,
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reward: model.strength,
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success: true
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});
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results.psychologicalModels++;
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}
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// Symbolic rules (logical inference)
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const symbolicRules = [
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{ rule: 'IF bias_detected THEN adjust_confidence', confidence: 0.92 },
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{ rule: 'IF heuristic_applied THEN verify_outcome', confidence: 0.88 }
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];
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for (const rule of symbolicRules) {
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await skills.createSkill({
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name: rule.rule,
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description: 'Symbolic reasoning rule',
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code: `function apply() { return "${rule.rule}"; }`,
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successRate: rule.confidence
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});
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results.symbolicRules++;
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}
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// Subsymbolic patterns (neural activations)
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for (let i = 0; i < 5; i++) {
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await reflexion.storeEpisode({
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sessionId: 'subsymbolic-pattern',
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task: `neural_activation_pattern_${i}`,
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reward: 0.80 + Math.random() * 0.15,
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success: true
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});
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results.subsymbolicPatterns++;
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}
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// Hybrid reasoning (combine psychological + symbolic + subsymbolic)
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results.hybridReasoning = psychModels.length + symbolicRules.length;
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const endTime = performance.now();
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results.totalTime = endTime - startTime;
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db.close();
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if (verbosity >= 2) {
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console.log(` 📊 Psychological Models: ${results.psychologicalModels}`);
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console.log(` 📊 Symbolic Rules: ${results.symbolicRules}`);
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console.log(` 📊 Subsymbolic Patterns: ${results.subsymbolicPatterns}`);
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console.log(` 📊 Hybrid Reasoning Instances: ${results.hybridReasoning}`);
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console.log(` ⏱️ Duration: ${results.totalTime.toFixed(2)}ms`);
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}
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return results;
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}
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};
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//# sourceMappingURL=psycho-symbolic-reasoner.js.map
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