Multi-Agent Collaboration Mechanisms: A Survey of LLMs
Reference: Tran, Dao, Nguyen, Pham, O’Sullivan, Nguyen (2025). arXiv:2501.06322. Source file: 2501.06322.pdf. URL
Summary
An extensive survey of LLM-based Multi-Agent Systems (MASs) focused on collaboration mechanisms. The authors propose an extensible framework characterising collaboration along five dimensions: actors (which agents), types (cooperation / competition / coopetition), structures (peer-to-peer, centralised, distributed), strategies (role-based vs model-based), and coordination protocols. They review methodologies across question answering, planning, debate, and role-play settings, and survey application domains including 5G/6G networks, Industry 5.0, and social simulation.
The survey explicitly positions itself as complementing prior single-agent or architecture-centric reviews by foregrounding collaboration channels — how agents actually talk, negotiate, and align — as the design pivot for scaling toward “artificial collective intelligence.”
Key Ideas
- Five-axis taxonomy of MAS collaboration: actors, types, structures, strategies, coordination protocols.
- Distinction between cooperative, competitive, and coopetitive channels as interaction primitives.
- Peer-to-peer vs centralised vs distributed MAS topologies map onto different coordination protocols.
- Role-based vs model-based strategies for dividing labour among specialised LLM agents.
- Open problems: scalability, evaluation benchmarks, cultural/social alignment of MAS behaviour.
Connections
- Survey Of Agent Interoperability Protocols
- Survey Of AI Agent Protocols
- LLM Agents
- Multi-Agent Systems
- Agent Communication Languages
- Model Context Protocol
- Agent-to-Agent Protocol
Conceptual Contribution
- Claim: Understanding LLM-based MAS requires a dedicated taxonomy of collaboration mechanisms, not just architectures or application domains; collaboration can be characterised along actors, types, structures, strategies, and protocols.
- Mechanism: Systematically reviews ~130 MAS works, maps each onto the five-dimension framework, then compares coordination protocols (debate, voting, role-play, tool-mediated) and draws lessons about scalability and emergence.
- Concepts introduced/used: Multi-Agent Systems, LLM Agents, Agent Communication Languages, Interoperability, Agent Discovery
- Stance: survey
- Relates to: Cited by Survey Of Agent Interoperability Protocols as prior art motivating its protocol-centric lens; offers a more behavioural counterpart to that paper’s structural comparison of MCP/ACP/A2A/ANP. Converges with Survey Of AI Agent Protocols on the need to treat protocols as ecosystems, not point-to-point specs.