LLM-based Multi-Agent Systems Survey
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A survey of the fast-growing LLM-based multi-agent systems space, covering both problem-solving applications and "world simulation" research.
Design dimensions: Characterizes MAS along axes like agent roles, communication protocols, memory architectures, and coordination strategies, giving a shared vocabulary for comparing systems.
Two application tracks: Separates problem-solving MAS (coding, debating, planning) from world-simulation MAS (social simulation, economic agents, game NPCs), which tend to use different design patterns.
Datasets and benchmarks: Catalogs the datasets used to evaluate MAS, including both cooperative and competitive benchmarks, and a live GitHub companion repository.
Challenges: Enumerates open issues - scalability of communication, stability of emergent behaviors, evaluation methodology, and safety of autonomous agent collectives.
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