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http://dx.doi.org/10.7583/JKGS.2016.16.6.79

Generation of AI Agent in Imperfect Information Card Games Using MCTS Algorithm: Focused on Hearthstone  

Oh, Pyeong (Graduate School, Dept. of Interaction Design, Hallym University)
Kim, Ji-Min (Graduate School, Dept. of Interaction Design, Hallym University)
Kim, Sun-Jeong (Graduate School, Dept. of Interaction Design, Hallym University)
Hong, Seokmin (Dept. of Advertising and Public Relations, Hallym University)
Publication Information
Journal of Korea Game Society / v.16, no.6, 2016 , pp. 79-90 More about this Journal
Abstract
Recently, many researchers have paid attention to the improved generation of AI agent in the area of game industry. Monte-Carlo Tree Search(MCTS) is one of the algorithms to search an optimal solution through random search with perfect information, and it is suitable for the purpose of calculating an approximate value to the solution of an equation which cannot be expressed explicitly. Games in Trading Card Game(TCG) genre such as the heartstone has imperfect information because the cards and play of an opponent are not predictable. In this study, MCTS is suggested in imperfect information card games so as to generate AI agents. In addition, the practicality of MCTS algorithm is verified by applying to heartstone game which is currently used.
Keywords
Monte-Carlo Tree Search; Artificial Intelligence; Finite State Machine; Behavior Tree; Hearthstone;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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