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English(EN) MARBO: Relational Belief Grounding for LLM Agents in Social Deduction Games

新的MARBO框架增强了大型语言模型智能体在社交推理游戏中的能力

研究人员开发了MARBO,一个新颖的大型语言模型(LLM)智能体框架,旨在提高其在社交推理游戏中的表现。这个多智能体关系信念优化(MARBO)系统明确地将智能体的行动和言语建立在关于隐藏角色和团队归属的关系信念基础上,解决了当前LLM智能体方法中常见的矛盾。实验表明,MARBO能够使精简的LLM智能体在不确定性场景中取得比现有方法更优越的性能。 AI

影响 这项研究可能促使LLM智能体在社交推理游戏等复杂、不确定的环境中表现出更具战略一致性和更强的能力。

排序理由 该集群描述了一篇详细介绍LLM智能体新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新的MARBO框架增强了大型语言模型智能体在社交推理游戏中的能力

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该集群描述了一篇详细介绍LLM智能体新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Hwang Yechan, Bae Sangjun, Kim Jeongmo, Bang Sangwoo, Han Seungyul ·

    MARBO:LLM 智能体在社交推理游戏中的关系信念基础

    arXiv:2609.06563v1 Announce Type: new Abstract: Social deduction games (SDGs) require agents to reason under partial observability by maintaining relational beliefs about hidden roles and team alignments. While recent LLM-agent approaches improve gameplay through prompting and pr…