Kréol Blouz

Wergin, Carsten

doi:10.7788/boehlau.9783412212599

Cited by 4 publications

(3 citation statements)

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“…The game of Skat is studied in many books [14], [6], [16], [11], [17], [18], [10]. Kupferschmid and Helmert developed the double-dummy skat solver (DDSS), a fast open card Skat game solver [19].…”

Section: Related Workmentioning

confidence: 99%

“…Many board games like Checkers [1], Nine-Men-Morris [2] have been solved already, or, as in Chess or Go, computer AIs are clearly outperforming humans [3], [4]. After some variants of Poker have also been solved to a satisfying degree [5], Skat [6] as well as Bridge [7] have been identified as two of the current game playing challenges in modern AIs [8], [9], given that expert human card players still play consistently better than the machines.…”

Section: Introductionmentioning

confidence: 99%

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On the Power of Refined Skat Selection

Edelkamp¹

2021

Preprint

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Skat is a fascinating combinatorial card game, show-casing many of the intrinsic challenges for modern AI systems such as cooperative and adversarial behaviors (among the players), randomness (in the deal), and partial knowledge (due to hidden cards). Given the larger number of tricks and higher degree of uncertainty, reinforcement learning is less effective compared to classical board games like Chess and Go. As within the game of Bridge, in Skat we have a bidding and trick-taking stage. Prior to the trick-taking and as part of the bidding process, one phase in the game is to select two skat cards, whose quality may influence subsequent playing performance drastically. This paper looks into different skat selection strategies. Besides predicting the probability of winning and other hand strength functions we propose hard expert-rules and a scoring functions based on refined skat evaluation features. Experiments emphasize the impact of the refined skat putting algorithm on the playing performance of the bots, especially for AI bidding and AI game selection.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Power of Refined Skat Selection

Edelkamp¹

2021

Preprint

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“…The game of Skat is considered in many books [14], [15], [16], [17], [18], [19]. A recent mathematical introduction to Skat playing has been given by [20].…”

Section: Related Workmentioning

confidence: 99%

Knowledge-Based Paranoia Search in Trick-Taking

Edelkamp¹

2021

Preprint

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This paper proposes knowledge-based paraonoia search (KBPS) to find forced wins during trick-taking in the card game Skat; for some one of the most interesting card games for three players. It combines efficient partial information game-tree search with knowledge representation and reasoning. This worstcase analysis, initiated after a small number of tricks, leads to a prioritized choice of cards. We provide variants of KBPS for the declarer and the opponents, and an approximation to find a forced win against most worlds in the belief space. Replaying thousands of expert games, our evaluation indicates that the AIs with the new algorithms perform better than humans in their play, achieving an average score of over 1,000 points in the agreed standard for evaluating Skat tournaments, the extended Seeger system.

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Von der Batarsité zum Welterbe: Die Maloya-Musik der Insel La Réunion

Wergin¹

2020

Musik – Kultur – Gedächtnis

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Kréol Blouz

Cited by 4 publications

References 0 publications

On the Power of Refined Skat Selection

On the Power of Refined Skat Selection

Knowledge-Based Paranoia Search in Trick-Taking

Von der Batarsité zum Welterbe: Die Maloya-Musik der Insel La Réunion

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