English(EN) Hierarchical Belief Modeling for Zero-Shot Opponent Adaptation in Partially Observable Multi-Agent Navigation

新智能体HORIZON通过分层信念建模增强多智能体导航能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-11 04:17

研究人员开发了HORIZON，一种专为Lux AI第三赛季竞赛设计的层级智能体，该竞赛要求在部分可观察的多智能体导航场景中进行适应。该智能体采用多方面方法，包括空间感知、信念跟踪、图注意力以及探索策略，将短期控制与长期推理分开。HORIZON使用JAX模拟器中的Proximal Policy Optimization进行训练，与现有基线相比，在胜率和适应能力方面均有显著提升。 AI

影响这项研究为复杂、部分可观察环境中的智能体适应引入了先进技术，可能影响未来的多智能体系统开发。

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arXiv cs.MA (Multiagent) TIER_1 English(EN) · Kejian Tong · 2026-09-11 04:17

面向部分可观察多智能体导航中零样本对手适应的分层信念建模

Lux AI Season 3 requires agents to act under partial observability, randomized episode level dynamics, and a best of five match structure that rewards both tactical execution and fast adaptation. We present HORIZON, a hierarchical agent that combines symmetry aware spatial percep…

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面向部分可观察多智能体导航中零样本对手适应的分层信念建模

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