EvolveMAS: A Unified Self-Evolution Framework for Decentralized Multi-Agent Systems
- Published
- Source
- arXiv
- Paper number
- 1379
- Field
- Agents
- arXiv ID
- 2610.34450
Key points
- EvolveMAS pairs each main agent with a dedicated MemoryAgent that maintains isolated Structured Memory outside the main agent's reasoning context.
- Across five benchmarks and six evaluation configurations, EvolveMAS achieves a normalized average score of 77.2, exceeding the strongest setting-specific baseline by 9.7 points and Self-Memory by 7.7 points.
- In the cooperative setting it records 83.0 on BBH and 97.0 on HumanEval, above the baselines of 79.0 and 95.7 respectively.
- In the adversarial Werewolf audit it achieves a wolf deception success of 70.0, exceeding the best competing method by 13 points.
- In the LLM-Deliberation ablation, an external MemoryAgent raises the unanimity rate from 24.0% to 74.0%, and cross-episode Knowledge raises it further to 86.0%.
- Memory governance keeps context occupancy at 0.62% at episode 7, lower than the 6.54% of carrying raw interaction histories.
Paper links
External research summaries. These are not HDATF publications or measured product results.