LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior
Embodied agents operating in decentralized and partially observable environments have attracted growing attention in recent years. However, existing large language model (LLM)-based agents often exhibit behaviors that are misaligned with their partners or inconsistent with the environment state, leading to inefficient cooperation and poor task success. To address this challenge, we propose a novel framework, Learning Laws of Cooperation (LLawCo), that enables embodied agents to autonomously alig
Record details
Published: 26 June 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Agents & autonomy · Environment
Retrieved: 14 July 2026
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ethics.ai (26 June 2026), “LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior,” evidence record 521, https://ethics.ai/record/521 (originally published by arXiv).
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