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AI agent achieves 51.35% win rate against champion using unsound search

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员为集换式卡牌游戏《Legends of Code and Magic》开发了一个智能体，该智能体利用不健全的搜索技术，在对阵游戏冠军ByteRL时取得了51.35%的胜率。该智能体名为NeteaseOPD，通过模仿学习和策略及价值前馈网络进行训练，并证明在引入搜索后，胜率显著提高了+24.6个百分点。此外，与ByteRL相比，该智能体在面对已发布的最佳响应攻击时表现出更强的韧性。 AI

影响 证明了不健全搜索在复杂不完美信息游戏中是有效的，可能影响未来的游戏AI开发。

排序理由 详细介绍游戏AI新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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AI agent achieves 51.35% win rate against champion using unsound search

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详细介绍游戏AI新方法的学术论文。[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) · Dustin Rubin ·

    Legends of Code and Magic 中基于策略和价值网络的非稳健搜索

    arXiv:2609.06816v1 Announce Type: new Abstract: Decision-time search in perfect and imperfect information games with enumerable belief states are effective methods for game AI. Collectible card games are imperfect information games with large belief states. Legends of Code and Ma…

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