The development of a simulated car racing controller based on Monte-Carlo tree search

Jia Hao Hou, Tsaipei Wang

研究成果: Conference contribution同行評審

摘要

Ever since its introduction, Monte Carlo Tree Search (MCTS) has shown very good performances on a number of games, most of which are turn-based zero-sum games. More recently, researchers have also started to expand the application of MCTS to other types of games. This paper proposes a new framework of applying MCTS to the game of simulated car racing. We choose to build the search tree in a discretized game-state space and then determine the action from the selected target game state. This allows us to avoid the need to discretize the action space. In addition, we are able to incorporate some heuristics on driving strategies naturally. The resulting controller shows very competitive performance in the open-source racing game TORCS.

原文English
主出版物標題TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面104-109
頁數6
ISBN(電子)9781509057320
DOIs
出版狀態Published - 16 3月 2017
事件2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016 - Hsinchu, Taiwan
持續時間: 25 11月 201627 11月 2016

出版系列

名字TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings

Conference

Conference2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016
國家/地區Taiwan
城市Hsinchu
期間25/11/1627/11/16

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