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Evidence record 10323 · automatically gathered

Multi-Agent LLMs Fail to Explore Each Other

Exploration is essential for reliable autonomy in multi-agent systems, yet it remains unclear whether large language model (LLM) agents can explore effectively when interacting with one another. We show that modern LLM agents fail to do so, often exhibiting myopic and polarized interaction patterns that lead to suboptimal coordination and increased regret. We formalize this challenge as the Multi-Agent Exploration problem, modeling it as a partially observable stochastic game (POSG) problem in w

Record details

Published: 13 July 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Agents & autonomy
Retrieved: 15 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (13 July 2026), “Multi-Agent LLMs Fail to Explore Each Other,” evidence record 10323, https://ethics.ai/record/10323 (originally published by HuggingFace Daily Papers).

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