Multi-Agent Transactive Memory
The Multi-Agent Transactive Memory (MATM) framework enables decentralized knowledge sharing among diverse LLM agents by storing and retrieving agent trajectories. Producer agents contribute procedural knowledge, which consumer agents can reuse to improve task performance. This system solves the problem of discarded agent experiences, creating a population-level experience sharing mechanism without needing joint training or coordination.