提出STORM框架，让多智能体协作时实时避免代码冲突。
Multi-agent Collaboration with State Management
- 通过状态管理在写入时检测并解决代码冲突
- 在两个基准上分别提升18.7和1.4分，成本相当或更低
- 可无缝接入任意多智能体系统，适合复杂任务协作
多智能体系统在解决复杂任务方面潜力巨大。然而，当多个智能体并发编辑共享代码库时，其修改可能无声冲突，导致视图不一致进而引发集成失败。现有系统通过工作区隔离（如每个智能体一个git worktree）应对，但将冲突解决推迟到事后合并阶段，恢复代价高。本文提出STORM（STate-ORiented Management），通过中介智能体与共享工作区的交互，确保每个智能体基于一致的代码视图操作，并在写入时检测和解决冲突。我们在Commit0和PaperBench上评估了STORM，使用多种LLM。相比基于git-worktree的基线，STORM在Commit0-Lite上提升+18.7，在PaperBench上提升+1.4，同时保持相当或更优的成本效率。结合单智能体运行，STORM在两个基准上分别达到87.6和78.2的最高分，表明显式状态管理比工作区隔离更适合作为多智能体协作的基础。STORM可无缝集成至任何多智能体系统。
原文摘要 · Abstract (English)
Recent advances in multi-agent systems have shown great potential for solving complex tasks. However, when multiple agents edit a shared codebase concurrently, their changes can silently conflict and inconsistent views lead to integration failures. Existing multi-agent systems address this through workspace isolation (e.g., one git worktree per agent), but this defers conflict resolution to a post-hoc merge step where recovery is expensive. In this paper, we propose STORM, i.e., STate-ORiented Management for multi-agent collaboration. Specifically, STORM manages agent states by mediating their interactions with the shared workspace, ensuring that each agent operates on a consistent view of the codebase and that conflicting edits are detected and resolved at write time. We evaluate STORM on Commit0 and PaperBench across multiple LLMs. STORM outperforms the git-worktree-based multi-agent baseline by +18.7 on Commit0-Lite and +1.4 on PaperBench, while achieving comparable or better cost efficiency. Combined with single-agent runs, STORM reaches highest scores of 87.6 and 78.2 on the two benchmarks respectively, suggesting that explicit state management is a more effective foundation for multi-agent collaboration than workspace isolation. STORM can also be plugged into any multi-agent system seamlessly.
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