Dang, Nguyen, Gent, Ian Philip, Nightingale, Peter orcid.org/0000-0002-5052-8634 et al. (2 more authors) (2025) Constraint Models for Klondike. In: 31st International Conference on Principles and Practice of Constraint Programming (CP 2025):. 31st International Conference on Principles and Practice of Constraint Programming, 10-15 Aug 2025, University of Glasgow. LIPICS , GBR (In Press)
Abstract
Klondike is the most famous single-player card game, and remains a challenging search problem even in the `thoughtful' variant where all card locations are known. We consider the full game of Klondike except for one restriction that the unusual move of `worrying back' is disallowed. This model is able to determine the winnability of all instances of the game and in practice does so in less than 2000 secs for 10,000 instances we tested, which no other known algorithm can achieve. On some instances, however, other techniques can produce answers more quickly. We use constraint modelling to produce schedules for running our constraint model in combination with other techniques. The combination outperforms any single solver across a range of time limits. Using this combination we are able to significantly improve the best estimate of winnability of Klondike without worrying back. Finally we show how we can use this work to also improve the estimate of winnability of the regular game of Klondike.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Nguyen Dang, Ian P. Gent, Peter Nightingale, Felix Ulrich-Oltean, Jack Waller. This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Funding Information: | Funder Grant number EPSRC EP/W001977/1 |
Depositing User: | Pure (York) |
Date Deposited: | 11 Jul 2025 13:00 |
Last Modified: | 12 Jul 2025 04:21 |
Status: | In Press |
Publisher: | LIPICS |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:229087 |