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• W3204602418 abstract "This paper provides practical guidelines for developing strong AI agents based on the Monte Carlo Tree Search algorithm in a game with imperfect information and/or randomness. These guidelines are backed up by series of experiments carried out in the very popular game - Hearthstone. Despite the focus on Hearthstone, the paper is written with reusability and universal applications in mind. For MCTS algorithm, we introduced a few novel ideas such as complete elimination of the so-called nature moves, separation of decision and simulation states as well as a multi-layered transposition table. These have helped to create a strong Hearthstone agent." @default.
• W3204602418 created "2021-10-11" @default.
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• W3204602418 date "2021-09-26" @default.
• W3204602418 modified "2023-10-18" @default.
• W3204602418 title "A Practical Solution to Handling Randomness and Imperfect Information in Monte Carlo Tree Search" @default.
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• W3204602418 doi "https://doi.org/10.15439/2021f3" @default.
• W3204602418 hasPublicationYear "2021" @default.
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