提出新搜索算法，在双人完美信息博弈中表现更优。
Study and improvement of search algorithms in two-players perfect information games
- 设计新搜索算法，优化博弈决策效率。
- 短时间搜索下，全游戏胜过所有对比算法。
- 适合追求高效博弈策略的AI研究者。
从数学角度看，游戏无处不在（如游戏产业、经济、国防、教育、化学、生物学等）。游戏中的搜索算法是人工智能用于博弈决策的方法。然而，目前尚无研究系统评估这些算法的通用性能。本文针对双人零和完美信息博弈填补这一空白，提出一种新型搜索算法。在大规模实验中，该算法在短时搜索下优于所有对比算法的所有游戏；在中等搜索时间内，优于22个测试游戏中的17个。
原文摘要 · Abstract (English)
Games, in their mathematical sense, are everywhere (game industries, economics, defense, education, chemistry, biology, ...).Search algorithms in games are artificial intelligence methods for playing such games. Unfortunately, there is no study on these algorithms that evaluates the generality of their performance. We propose to address this gap in the case of two-player zero-sum games with perfect information. Furthermore, we propose a new search algorithm and we show that, for a short search time, it outperforms all studied algorithms on all games in this large experiment and that, for a medium search time, it outperforms all studied algorithms on 17 of the 22 studied games.
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