Enhancements for Real-Time Monte-Carlo Tree Search in General Video Game Playing

Dennis J. N. J. Soemers*, Chiara F. Sironi, Torsten Schuster, Mark H. M. Winands

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

11 Citations (Web of Science)
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Abstract

General Video Game Playing (GVGP) is a field of Artificial Intelligence where agents play a variety of real-time video games that are unknown in advance. This limits the use of domain-specific heuristics. Monte-Carlo Tree Search (MCTS) is a search technique for game playing that does not rely on domain-specific knowledge. This paper discusses eight enhancements for MCTS in GVGP; Progressive History, N-Gram Selection Technique, Tree Reuse, Breadth-First Tree Initialization, Loss Avoidance, Novelty-Based Pruning, Knowledge-Based Evaluations, and Deterministic Game Detection. Some of these are known from existing literature, and are either extended or introduced in the context of GVGP, and some are novel enhancements for MCTS. Most enhancements are shown to provide statistically significant increases in win percentages when applied individually. When combined, they increase the average win percentage over sixty different games from 31.0% to 48.4% in comparison to a vanilla MCTS implementation, approaching a level that is competitive with the best agents of the GVG-AI competition in 2015.
Original languageEnglish
Title of host publication2016 IEEE Conference on Computational Intelligence and Games (CIG)
PublisherIEEE
Pages436-443
Number of pages8
DOIs
Publication statusPublished - Sep 2016
Event2016 IEEE Conference on Computational Intelligence and Games (CIG) - Petros M. Nomikos Conference Centre, Santorini, Greece
Duration: 20 Sep 201623 Sep 2016

Publication series

SeriesIEEE Conference on Computational Intelligence and Games
ISSN2325-4270

Conference

Conference2016 IEEE Conference on Computational Intelligence and Games (CIG)
Country/TerritoryGreece
CitySantorini
Period20/09/1623/09/16

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