English(EN) Efficient Generation of Diverse Cooperative Agents with World Models

新的XPM-WM框架利用世界模型提高AI智能体训练效率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 04:00

研究人员开发了一个名为XPM-WM的新框架，该框架显著提高了训练协作式AI智能体的效率。该方法利用学习到的世界模型（WM）来生成模拟轨迹，从而绕过了基于种群的训练（PBT）方法（如交叉博弈最小化（XPM））通常需要的计算成本高昂的混合博弈轨迹。通过消除这一瓶颈并引导智能体训练，XPM-WM展示了卓越的样本效率，并与种群规模呈线性扩展，有效地生成了多样化且高性能的协作智能体。 AI

影响通过减少训练时间和计算成本，加速了协作式AI智能体的开发和部署。

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arXiv cs.AI TIER_1 English(EN) · Yi Loo, Akshunn Trivedi, Malika Meghjani · 2026-10-27 04:00

使用世界模型高效生成多样化的协作代理

arXiv:2506.07450v2 Announce Type: replace Abstract: A major bottleneck in the training process for Zero-Shot Coordination (ZSC) agents is the generation of diverse partner agents via Population-based Training (PBT). Prominent PBT methods, such as Cross-play Minimization (XPM), ca…

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使用世界模型高效生成多样化的协作代理

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