Classical methods such as a* and ida* are a popular and successful choice for one-player games. However, they fail without an accurate admissible evaluation function. In this paper we investigate whether monte-carlo tree search (mcts) is an interesting alternative for one-player games where a* and ida* methods do not perform well. Therefore, we propose a new mcts variant, called single-player monte-carlo tree search (sp-mcts). The selection and backpropagation strategy in sp-mcts are different from standard mcts. Moreover, sp-mcts makes use of a straightforward meta-search extension. We tested the method on the puzzle samegame. It turned out that our sp-mcts program gained the highest score so far on the standardized test set.
|Title of host publication||Computers and Games|
|Subtitle of host publication||6th International Conference, CG 2008, Beijing, China, September 29 - October 1, 2008. Proceedings|
|Place of Publication||Berlin, Heidelberg|
|Number of pages||12|
|Publication status||Published - 2008|
|Series||Lecture Notes in Computer Science|