Combining prediction of human decisions with ISMCTS in imperfect information games

Moshe Bitan, Sarit Kraus

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

3 Scopus citations

Abstract

We present agents that perform well against humans in imperfect information games with partially observable actions. We introduce the Semi-Determinized-MCTS (SDMCTS), a variant of the Information Set MCTS algorithm (ISMCTS). SDMCTS generates a predictive model of the unobservable portion of the opponent's actions from historical behavioral data. Next, SDMCTS performs simulations on an instance of the game where the unobservable portion of the opponent's actions are determined. Thereby, it facilitates the use of the predictive model in order to decrease uncertainty. We present an implementation of the SDMCTS applied to the Cheat Game. Results from experiments with 120 subjects playing a head-to-head Cheat Game against our SDMCTS agents suggest that SDMCTS performs well against humans, and its performance improves as the predictive model's accuracy increases.

Original languageEnglish
Title of host publication17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1874-1876
Number of pages3
ISBN (Print)9781510868083
StatePublished - 2018
Event17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018 - Stockholm, Sweden
Duration: 10 Jul 201815 Jul 2018

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume3
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
Country/TerritorySweden
CityStockholm
Period10/07/1815/07/18

Bibliographical note

Publisher Copyright:
© 2018 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

Keywords

  • Agents competing against humans

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