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English(EN) Tensor-Coord: Algebraic Decomposition of Joint Plan Tensors for Conflict-Free Multi-Agent LLM Planning

Tensor-Coord 框架使用多线性代数实现无冲突多智能体LLM规划

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了 Tensor-Coord，一个利用多线性代数来表示和分解多个大型语言模型生成的联合规划的新框架。该方法将联合规划分解为张量，从而无需领域特定规则即可识别协调结构和冲突分数。实验表明，Tensor-Coord 可以显著提高多智能体场景下无冲突规划的收敛速度，成功率因涉及的智能体数量而异。 AI

影响 引入了一种新颖的代数分解方法来解决多智能体LLM规划中的协调失败问题。

排序理由 该集群包含一篇详细介绍多智能体LLM规划新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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Tensor-Coord 框架使用多线性代数实现无冲突多智能体LLM规划

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该集群包含一篇详细介绍多智能体LLM规划新方法的论文。[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) · Mudit Rastogi ·

    Tensor-Coord: 联合规划张量的代数分解，实现无冲突多智能体LLM规划

    arXiv:2606.16478v1 Announce Type: new Abstract: Large language models (LLMs) remain limited in multi-agent planning because independently generated plans can create coordination failures such as spatial collisions, resource contention, and temporal deadlocks. We introduce Tensor-…

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