Agent Memory System

Overview

agent-memory-system provides persistent memory architecture enabling AI agents to remember across sessions, learn from experience, and build long-term knowledge.

Purpose: Enable true continuous improvement through persistent memory

Pattern: Capabilities-based (4 memory types with independent operations)

Key Innovation: Multi-layered memory architecture (episodic, procedural, semantic, short-term) enabling agents to learn and adapt over time

Core Principles:

1. Episodic Memory - Remember specific past events and decisions
2. Procedural Memory - Learn and improve skills over time
3. Semantic Memory - Build knowledge graphs of facts and relationships
4. Short-Term Memory - Active working context