Comparison of rapid action value estimation variants for general game playing

@article{Sironi2016ComparisonOR,
  title={Comparison of rapid action value estimation variants for general game playing},
  author={Chiara F. Sironi and Mark H. M. Winands},
  journal={2016 IEEE Conference on Computational Intelligence and Games (CIG)},
  year={2016},
  pages={1-8}
}
General Game Playing (GGP) aims at creating computer programs able to play any arbitrary game at an expert level given only its rules. The lack of game-specific knowledge and the necessity of learning a strategy online have made Monte-Carlo Tree Search (MCTS) a suitable method to tackle the challenges of GGP. An efficient search-control mechanism can substantially increase the performance of MCTS. The RAVE strategy and its more recent variant, GRAVE, have been proposed for this reason. In this… CONTINUE READING

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