Monte Carlo Tree Search for Asymmetric Trees

Exploiting graph properties of game trees

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Finite-time analysis of the multiarmed bandit problem

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Efficient selectivity and backup operators in Monte-Carlo tree search

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Bandit based monte-carlo planning

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On the parallelization of UCT

Cazenave, T. and Jouandeau, N. (2007) · 2007

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Monte-Carlo Tree Search: A New Framework for Game AI

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Multi-armed bandits with episode context

Rosin, C. D. (2011) · 2011

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A survey of monte carlo tree search methods

Browne, C. B., Powley, E., Whitehouse, D., Lucas, S. M., Cowling, P. I., Rohlfshagen, P., Tavener, S., Perez, D., Samothrakis, S., and Colton, S. (2012) · 2012

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Deep learning for real-time Atari game play using offline Monte-Carlo tree search planning

Guo, X., Singh, S., Lee, H., Lewis, R. L., and Wang, X. (2014) · 2014

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From bandits to Monte-Carlo Tree Search: The optimistic principle applied to optimization and planning

Munos, R. et al. (2014) · 2014

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Generalization and Exploration via Randomized Value Functions

Osband, I., Van Roy, B., and Wen, Z. (2016) · 2016

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Mastering the game of Go with deep neural networks and tree search

Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al. (2016) · 2016

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Mastering the game of go without human knowledge

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Reinforcement learning: An Introduction

Original

Sutton, R. S. and Barto, A. G. (2018) · 2018

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