Abstract
Monte-Carlo tree search, especially the UCT algorithm and its enhancements, have become extremely popular. Because of the importance of this family of algorithms, a deeper understanding of when and how the different enhancements work is desirable. To avoid the hard to analyze intricacies of tournament-level programs in complex games, this work focuses on a simple abstract game, which is designed to be ideal for history-based heuristics such as RAVE. Experiments show the influence of game complexity and of enhancements on the performance of Monte-Carlo Tree Search. © 2010 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Tom, D., & Müller, M. (2010). A study of UCT and its enhancements in an artificial game. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6048 LNCS, pp. 55–64). https://doi.org/10.1007/978-3-642-12993-3_6
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
