tasq/node_modules/agentdb/dist/simulation/scenarios/research-swarm.js

/**
 * Research-Swarm Integration
 *
 * Distributed research graph DB
 * Integration with research-swarm package
 *
 * Features:
 * - Collaborative research agents
 * - Literature review aggregation
 * - Hypothesis generation and testing
 * - Knowledge synthesis
 */
import { createUnifiedDatabase } from '../../src/db-unified.js';
import { ReflexionMemory } from '../../src/controllers/ReflexionMemory.js';
import { CausalMemoryGraph } from '../../src/controllers/CausalMemoryGraph.js';
import { SkillLibrary } from '../../src/controllers/SkillLibrary.js';
import { EmbeddingService } from '../../src/controllers/EmbeddingService.js';
import * as path from 'path';
export default {
    description: 'Research-swarm distributed research with collaborative agents',
    async run(config) {
        const { verbosity = 2, researchers = 5 } = config;
        if (verbosity >= 2) {
            console.log(`   🔬 Initializing Research-Swarm (${researchers} researchers)`);
        }
        // Initialize distributed research graph database
        const embedder = new EmbeddingService({
            model: 'Xenova/all-MiniLM-L6-v2',
            dimension: 384,
            provider: 'transformers'
        });
        await embedder.initialize();
        const db = await createUnifiedDatabase(path.join(process.cwd(), 'simulation', 'data', 'advanced', 'research-swarm.graph'), embedder, { forceMode: 'graph' });
        const reflexion = new ReflexionMemory(db.getGraphDatabase(), embedder, undefined, undefined, db.getGraphDatabase());
        const causal = new CausalMemoryGraph(db.getGraphDatabase(), db.getGraphDatabase());
        const skills = new SkillLibrary(db.getGraphDatabase(), embedder, undefined, db.getGraphDatabase());
        const results = {
            papers: 0,
            hypotheses: 0,
            experiments: 0,
            synthesizedKnowledge: 0,
            totalTime: 0
        };
        const startTime = performance.now();
        // Literature Review (each researcher finds papers)
        const papers = [
            'neural_architecture_search_techniques',
            'few_shot_learning_methods',
            'transfer_learning_strategies',
            'meta_learning_algorithms',
            'continual_learning_approaches'
        ];
        const paperIds = [];
        for (let i = 0; i < papers.length; i++) {
            const id = await reflexion.storeEpisode({
                sessionId: `researcher-${i % researchers}`,
                task: `literature_review: ${papers[i]}`,
                reward: 0.80 + Math.random() * 0.15, // Quality varies
                success: true,
                input: 'academic_search',
                output: `paper_summary_${papers[i]}`
            });
            paperIds.push(id);
            results.papers++;
        }
        // Hypothesis Generation (synthesizing from papers)
        const hypotheses = [
            'combining_meta_learning_with_architecture_search_improves_few_shot',
            'transfer_learning_enables_faster_continual_learning',
            'meta_architecture_search_reduces_hyperparameter_tuning'
        ];
        const hypothesisIds = [];
        for (const hypothesis of hypotheses) {
            const id = await reflexion.storeEpisode({
                sessionId: 'research-synthesis',
                task: `hypothesis: ${hypothesis}`,
                reward: 0.70, // Untested hypothesis
                success: false, // Not yet validated
                input: 'literature_synthesis',
                output: `hypothesis_${hypothesis}`,
                critique: 'Requires experimental validation'
            });
            hypothesisIds.push(id);
            results.hypotheses++;
            // Link hypothesis to supporting papers
            for (let i = 0; i < Math.min(2, paperIds.length); i++) {
                await causal.addCausalEdge({
                    fromMemoryId: paperIds[i],
                    fromMemoryType: 'episode',
                    toMemoryId: id,
                    toMemoryType: 'episode',
                    similarity: 0.85,
                    uplift: 0.20,
                    confidence: 0.80,
                    sampleSize: 100,
                    mechanism: 'paper_supports_hypothesis'
                });
            }
        }
        // Experimental Validation
        const experiments = [
            { hypothesis: 0, result: 'confirmed', confidence: 0.92 },
            { hypothesis: 1, result: 'confirmed', confidence: 0.88 },
            { hypothesis: 2, result: 'partially_confirmed', confidence: 0.75 }
        ];
        for (const exp of experiments) {
            await reflexion.storeEpisode({
                sessionId: 'experimental-validation',
                task: `experiment_validate_hypothesis_${exp.hypothesis}`,
                reward: exp.confidence,
                success: exp.result === 'confirmed',
                input: `hypothesis_${exp.hypothesis}`,
                output: exp.result,
                critique: `Confidence: ${exp.confidence}`
            });
            results.experiments++;
        }
        // Knowledge Synthesis (create reusable research methods)
        const researchMethods = [
            'meta_architecture_search_protocol',
            'few_shot_evaluation_framework',
            'transfer_learning_pipeline'
        ];
        for (const method of researchMethods) {
            await skills.createSkill({
                name: method,
                description: 'Research methodology',
                code: `// Reusable research method: ${method}`,
                successRate: 0.85
            });
            results.synthesizedKnowledge++;
        }
        const endTime = performance.now();
        results.totalTime = endTime - startTime;
        db.close();
        if (verbosity >= 2) {
            console.log(`      📊 Papers Reviewed: ${results.papers}`);
            console.log(`      📊 Hypotheses Generated: ${results.hypotheses}`);
            console.log(`      📊 Experiments Conducted: ${results.experiments}`);
            console.log(`      📊 Synthesized Knowledge: ${results.synthesizedKnowledge} methods`);
            console.log(`      ⏱️  Duration: ${results.totalTime.toFixed(2)}ms`);
        }
        return results;
    }
};
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