New MARBO Framework Enhances LLM Agents in Social Deduction Games

Researchers have developed MARBO, a novel framework for Large Language Model (LLM) agents designed to improve performance in social deduction games. This Multi-Agent Relational Belief Optimization (MARBO) system explicitly grounds agent actions and speech in relational beliefs about hidden roles and team alignments, addressing inconsistencies common in current LLM-agent approaches. Experiments demonstrate that MARBO enables compact LLM agents to achieve superior performance compared to existing methods, particularly in scenarios involving uncertainty. AI

IMPACT This research could lead to more strategically consistent and capable LLM agents in complex, uncertain environments like social deduction games.

RANK_REASON The cluster describes a new research paper detailing a novel framework for LLM agents. [lever_c_demoted from research: ic=1 ai=1.0]

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• alphaXiv
• arXiv
• CatalyzeX
• DagsHub
• Gotit.pub
• Hugging Face
• LLM Agents
• Multi-Agent Relational Belief Optimization
• ScienceCast
• Social Deduction Games

• paper
• model release

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