在部分可观察博弈中学习开局：在Phantom Go中使用随机种子
Learning opening books in partially observable games: using random seeds in Phantom Go
摘要：
许多人工智能（AI）都是随机的。一个人可以幸运或不幸的随机种子;我们量化这种影响，并表明，也许与直觉相反，这是远远不能忽略不计的。然后，我们采用两种不同的现有算法选择好的种子和种子的概率分布。这主要是为了学习一本开篇的书。我们将此应用于幻影围棋，这和所有幻影游戏一样，很难打开书本学习。我们将5x 5对相同AI的胜率从50%提高到70%，并将5x 5，7 x7和9 x9对更强（学习）对手的胜率从大约0%提高到40%。
英文摘要：
Many artificial intelligences (AIs) are randomized. One can be lucky or unlucky with the random seed; we quantify this effect and show that, maybe contrarily to intuition, this is far from being negligible. Then, we apply two different existing algorithms for selecting good seeds and good probability distributions over seeds. This mainly leads to learning an opening book. We apply this to Phantom Go, which, as all phantom games, is hard for opening book learning. We improve the winning rate from 50% to 70% in 5x5 against the same AI, and from approximately 0% to 40% in 5x5, 7x7 and 9x9 against a stronger (learning) opponent.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
