reasoningbank-adaptive-learning-with-agentdblisted

# ReasoningBank Adaptive Learning with AgentDB ## Overview Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database for trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Build self-learning agents that improve decision-making through experience. ## SOP Framework: 5-Phase Adaptive Learning ### Phase 1: Initialize ReasoningBank (1-2 hours) - Setup AgentDB with ReasoningBank - Configure trajectory tracking - Initialize verdict system ### Phase 2: Track Trajectories (2-3 hours) - Record agent decisions - Store reasoning paths - Capture context and outcomes ### Phase 3: Judge Verdicts (2-3 hours) - Evaluate decision quality - Score reasoning paths - Identify successful patterns ### Phase 4: Distill Memory (2-3 hours) - Extract learned patterns - Consolidate successful strategies - Prune ineffective approaches ### Phase 5: Apply Learning (1-2 hours) - Use learned patterns in decisions - Improve future reasoning - Measure improvement ## Quick Start ```typescript import { AgentDB, ReasoningBank } from 'reasoningbank-agentdb'; // Initialize const db = new AgentDB({ name: 'reasoning-db', dimensions: 768, features: { reasoningBank: true } }); const reasoningBank = new ReasoningBank({ database: db, trajectoryWindow: 1000, verdictThreshold: 0.7 }); // Track trajectory await reasoningBank.trackTrajectory({ agent: 'agent-1', decision: 'action-A', reasoning: 'Because X and Y', context: { state: cu