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Many artificial intelligences (AIs) are randomized. One can be lucky orunlucky with the random seed; we quantify this effect and show that, maybecontrarily to intuition, this is far from being negligible. Then, we apply twodifferent existing algorithms for selecting good seeds and good probabilitydistributions over seeds. This mainly leads to learning an opening book. Weapply this to Phantom Go, which, as all phantom games, is hard for opening booklearning. We improve the winning rate from 50% to 70% in 5x5 against the sameAI, and from approximately 0% to 40% in 5x5, 7x7 and 9x9 against a stronger(learning) opponent.

Learning opening books in partially observable games: using random seeds in Phantom Go