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LLM agents struggle with zero-shot coordination

Original title: Zero-Shot Coordination among LLM Agents

arXiv cs.AI / cs.LG / cs.CLby Adrian Hayler ()1 min read
AI summary · x-ai/grok-4.7Summaries by Vani AI

Frontier LLM agents fail to coordinate due to weak reasoning about partner beliefs in simple controlled settings.

We study zero-shot coordination where independently developed agents must coordinate at test time. Far less is known about LLM agent performance despite increasing deployment. Existing work relies on specialised scaffolding unlikely to be shared in practice. We focus on simple general-purpose scaffolds in minimal environments designed to isolate coordination challenges. Our results show frontier LLM agents struggle largely due to limited understanding of the coordination problem and weak reasoning about their partner's beliefs. While LLMs introduce semantic information as an additional axis they fail to exploit this structure effectively. We propose Coordination-friendly definitions as a principled approach and show they can be discovered automatically.

Key facts
  • LLM agents struggle to coordinate even in controlled minimal environments
  • Failure stems from limited understanding and weak reasoning about partner beliefs
  • Semantic information is introduced but not effectively exploited
  • Coordination-friendly definitions can be discovered automatically
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From the original article

1 min read at arxiv.org

We study zero-shot coordination (ZSC), where independently developed agents must coordinate at test time. While ZSC has been well studied in the RL literature, far less is known about the performance of LLM agents despite their increasing deployment in such settings. Existing work on LLM coordination often relies on specialised scaffolding that independently developed agents are unlikely to share in practice.

arXiv cs.AI / cs.LG / cs.CL

By Adrian Hayler · arxiv.org

Read the full article at arXiv cs.AI / cs.LG / cs.CL

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