Pruning Stochastic Game Trees Using Neural Networks for Reduced Action Space Approximation
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- Julian Schrittwieser & Ioannis Antonoglou & Thomas Hubert & Karen Simonyan & Laurent Sifre & Simon Schmitt & Arthur Guez & Edward Lockhart & Demis Hassabis & Thore Graepel & Timothy Lillicrap & David , 2020. "Mastering Atari, Go, chess and shogi by planning with a learned model," Nature, Nature, vol. 588(7839), pages 604-609, December.
- Michael N. Katehakis & Arthur F. Veinott, 1987. "The Multi-Armed Bandit Problem: Decomposition and Computation," Mathematics of Operations Research, INFORMS, vol. 12(2), pages 262-268, May.
- David Silver & Julian Schrittwieser & Karen Simonyan & Ioannis Antonoglou & Aja Huang & Arthur Guez & Thomas Hubert & Lucas Baker & Matthew Lai & Adrian Bolton & Yutian Chen & Timothy Lillicrap & Fan , 2017. "Mastering the game of Go without human knowledge," Nature, Nature, vol. 550(7676), pages 354-359, October.
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Keywords
Monte Carlo Tree Search; pruning; neural networks; multi-armed bandit; Upper Confidence Bound; Hearthstone;All these keywords.
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