Combining UCT and Nested Monte Carlo Search for Single-Player General Game Playing

  title={Combining UCT and Nested Monte Carlo Search for Single-Player General Game Playing},
  author={Jean M{\'e}hat and Tristan Cazenave},
  journal={IEEE Transactions on Computational Intelligence and AI in Games},
Monte Carlo tree search (MCTS) has been recently very successful for game playing, particularly for games where the evaluation of a state is difficult to compute, such as Go or General Games. We compare nested Monte Carlo (NMC) search, upper confidence bounds for trees (UCT-T), UCT with transposition tables (UCT+T), and a simple combination of NMC and UCT+T (MAX) on single-player games of the past General Game Playing (GGP) competitions. We show that transposition tables improve UCT and that… CONTINUE READING
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General game playing: Game description language specification

  • N. Love, T. Hinrichs, M. Genesereth
  • Technical report, Stanford University,
  • 2006
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