Sequential halving for partially observable games

Tom Pepels, Tristan Cazenave, Mark H M Winands

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

Abstract

This paper investigates Sequential Halving as a selection policy in the following four partially observable games: Go Fish, Lost Cities, Phantom Domineering, and Phantom Go. Additionally, H-MCTS is studied, which uses Sequential Halving at the root of the search tree, and UCB elsewhere. Experimental results reveal that H-MCTS performs the best in Go Fish, whereas its performance is on par in Lost Cities and Phantom Domineering. Sequential Halving as a at Monte-Carlo Search appears to be the stronger technique in Phantom Go.
Original languageEnglish
Title of host publicationComputer Games
PublisherSpringer
Pages16-29
Number of pages14
ISBN (Print)9783319394015
DOIs
Publication statusPublished - 2016

Publication series

SeriesCommunications in Computer and Information Science
Volume614

Cite this

Pepels, T., Cazenave, T., & Winands, M. H. M. (2016). Sequential halving for partially observable games. In Computer Games (pp. 16-29). Springer. Communications in Computer and Information Science, Vol.. 614 https://doi.org/10.1007/978-3-319-39402-2_2