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Mastering the game of Go without human knowledge
www.ics.uci.eduuation. The policy network was trained initially by supervised learn ing to accurately predict human expert moves, and was subsequently refined by policygradient reinforcement learning. The value network was trained to predict the winner of games played by the policy net work against itself. Once trained, these networks were combined with