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English(EN) Conservative Policy Iteration For Zero-Sum POSGs

新算法通过保守策略更新改进零和POSG求解

研究人员开发了一种新颖的近似策略迭代算法,专门用于有限时间范围内的零和部分可观随机博弈(zs-POSGs)。该方法为每个玩家维护一个策略并联合更新它们,将计算集中在可利用的占用区域上。该算法在局部策略改进、保守更新和持续探索之间交替进行,在基准测试中表现出竞争力,并且与PBVI、HSVI和CFR+等现有求解器相比,通常能改善运行时间-可利用性权衡。 AI

影响 引入了一种解决复杂博弈论问题的新颖算法方法,可能影响多智能体系统和不确定性下决策的AI研究。

排序理由 学术论文,详细介绍了一种针对特定类型博弈论问题的新算法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新算法通过保守策略更新改进零和POSG求解

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学术论文,详细介绍了一种针对特定类型博弈论问题的新算法。[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) · Erwan C. Escudie, Matthia Sabatelli, Jilles Steeve Dibangoye ·

    零和部分可观察随机博弈的保守策略迭代

    arXiv:2610.36847v1 Announce Type: new Abstract: Occupancy-state reductions make dynamic programming possible for zero-sum partially observable stochastic games (zs-POSGs). Existing point-based solvers usually optimise a central value function. This restores Bellman recursion, but…