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Assessing Simultaneous Action Selection and Complete Information in TAG with Sushi Go!
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-7738-1601
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-3924-7484
2021 (English)In: Proceedings of the 3rd Conference on Games, IEEE, 2021Conference paper, Published paper (Refereed)
Abstract [en]

Digitalizing tabletop games for general game playing(GGP) AI research is a continuously growing field. TabletopGames Framework (TAG) is a framework developed to simplifythe process of implementing tabletop board games to digital form.Sushi Go! is a game that combines simultaneous action selectionand complete information. This creates a unique combination ofmechanics, which presents a new challenge for GGP agents. Byimplementing Sushi Go! into TAG, we can test different agent’sperformance using these mechanics and compare them to theirexisting performances in the other games of TAG. Results ofthis testing are presented, which display that the framework iscapable of implementing Sushi Go! and that the agents performwith mixed results. Further developing heuristics for the agentsshould prove to increase their performance when faced with thesetypes of games.

Place, publisher, year, edition, pages
IEEE, 2021.
Series
IEEE Conference on Computational Intelligence and Games, ISSN 2325-4270, E-ISSN 2325-4289
Keywords [en]
General Game Playing, Tabletop Games, Game AI
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mau:diva-47272DOI: 10.1109/CoG52621.2021.9618987ISI: 000842962500148Scopus ID: 2-s2.0-85122963476ISBN: 978-1-6654-3886-5 (electronic)ISBN: 978-1-6654-4608-2 (print)OAI: oai:DiVA.org:mau-47272DiVA, id: diva2:1617702
Conference
IEEE Conference on Games (CoG), 17-20 Aug. 2021, Copenhagen, Denmark
Available from: 2021-12-07 Created: 2021-12-07 Last updated: 2023-12-28Bibliographically approved

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Alvarez, AlbertoFont, Jose

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