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Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game Jass
Document Image and Voice Analysis Group (DIVA), University of Fribourg, Switzerland.
Document Image and Voice Analysis Group (DIVA), University of Fribourg, Switzerland.
Document Image and Voice Analysis Group (DIVA), University of Fribourg, Switzerland.
Document Image and Voice Analysis Group (DIVA), University of Fribourg, Switzerland.
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2019 (English)In: Proceedings 6th Swiss Conference on Data Science: SDS2019, IEEE, 2019, p. 25-30Conference paper, Published paper (Refereed)
Abstract [en]

In the last decades we have witnessed the success of applications of Artificial Intelligence to playing games. In this work we address the challenging field of games with hidden information and card games in particular. Jass is a very popular card game in Switzerland and is closely connected with Swiss culture. To the best of our knowledge, performances of Artificial Intelligence agents in the game of Jass do not outperform top players yet. Our contribution to the community is two-fold. First, we provide an overview of the current state-of-the-art of Artificial Intelligence methods for card games in general. Second, we discuss their application to the use-case of the Swiss card game Jass. This paper aims to be an entry point for both seasoned researchers and new practitioners who want to join in the Jass challenge.

Place, publisher, year, edition, pages
IEEE, 2019. p. 25-30
Keywords [en]
Jass, Artificial Intelligence, Hidden Information, Reinforcement Learning, Card Games
National Category
Computer Sciences
Research subject
Machine Learning
Identifiers
URN: urn:nbn:se:ltu:diva-85982DOI: 10.1109/SDS.2019.00-12ISI: 000502813100005Scopus ID: 2-s2.0-85071369644OAI: oai:DiVA.org:ltu-85982DiVA, id: diva2:1573130
Conference
6th Swiss Conference on Data Science (SDS2019), Bern, Switzerland, June 14, 2019
Note

ISBN för värdpublikation: 978-1-7281-3105-4

Available from: 2021-06-24 Created: 2021-06-24 Last updated: 2022-04-11Bibliographically approved

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Liwicki, Marcus

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  • apa
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Output format
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