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English(EN) PokaiTrainer: Scaling Belief-State Search to Competitive Pok\'emon VGC

AI代理通过信念状态搜索应对复杂的宝可梦VGC

研究人员开发了PokaiTrainer,一个能够参加复杂的宝可梦VGC双打比赛的AI代理。该系统利用PokaiEngine,一个基于Rust的对战引擎,可以有效地计算联合行动的完整结果分布。PokaiTrainer将Student of Games方法应用于处理VGC的规模,将每个决策视为计算预算内的贝叶斯矩阵博弈。该代理在Showdown排行榜上对阵人类玩家的胜率为59%,最高Elo评分达到前500名。 AI

影响 展示了先进的AI搜索技术在高度复杂、多代理、同步动作游戏环境中的应用。

排序理由 该项目是一篇研究论文,详细介绍了一个新的AI代理及其复杂游戏的底层引擎。[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 →

AI代理通过信念状态搜索应对复杂的宝可梦VGC

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该项目是一篇研究论文,详细介绍了一个新的AI代理及其复杂游戏的底层引擎。[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) · Max Yu ·

    PokaiTrainer:将信念状态搜索扩展到竞技宝可梦VGC

    arXiv:2608.29197v1 Announce Type: cross Abstract: Decision-time equilibrium search carried poker to superhuman play, but it has so far relied on tractable subgames: a handful of actions per decision, chance confined to card deals, one player moving at a time. Competitive Pok\'emo…