4 Search Results for "Ulrich-Oltean, Felix"

Document
DOI: 10.4230/LIPIcs.CP.2025.9
Constraint Models for Klondike

Authors: Nguyen Dang, Ian P. Gent, Peter Nightingale, Felix Ulrich-Oltean, and Jack Waller

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

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.
Cite as

Nguyen Dang, Ian P. Gent, Peter Nightingale, Felix Ulrich-Oltean, and Jack Waller. Constraint Models for Klondike. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 9:1-9:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{dang_et_al:LIPIcs.CP.2025.9,
  author =	{Dang, Nguyen and Gent, Ian P. and Nightingale, Peter and Ulrich-Oltean, Felix and Waller, Jack},
  title =	{{Constraint Models for Klondike}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{9:1--9:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.9},
  URN =		{urn:nbn:de:0030-drops-238702},
  doi =		{10.4230/LIPIcs.CP.2025.9},
  annote =	{Keywords: AI Planning, Modelling, Constraint Programming, Solitaire and Patience Games}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.CP.2025.43
Scheduling Telescope Observations for the European Southern Observatory (Short Paper)

Authors: Michael Prümm, Peter Nightingale, and Felix Ulrich-Oltean

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
The European Southern Observatory (ESO) provides state-of-the-art large telescope facilities at three sites in Chile, supported by 16 European member states. Astronomers submit proposals for sets of observations which are reviewed and ranked based on scientific merit, then a schedule is constructed respecting the ranking and aiming to make the fullest use of the various telescopes and numerous instruments. Currently a schedule covers six months, but in the near future ESO will switch to annual schedules. Here we examine the most challenging scheduling problem encountered by ESO: scheduling the operations of the Very Large Telescope Interferometer (VLTI) on Paranal, Chile. Tasks to be scheduled include observations performed by ESO staff, "visitor mode" periods where astronomers visit the site to use the telescopes, various maintenance tasks, and reconfiguration tasks taking multiple days. Typically a VLTI six-month schedule would contain approximately 450 activities. We explore global constraint models and a SAT encoding of the problem.
Cite as

Michael Prümm, Peter Nightingale, and Felix Ulrich-Oltean. Scheduling Telescope Observations for the European Southern Observatory (Short Paper). In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 43:1-43:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{prumm_et_al:LIPIcs.CP.2025.43,
  author =	{Pr\"{u}mm, Michael and Nightingale, Peter and Ulrich-Oltean, Felix},
  title =	{{Scheduling Telescope Observations for the European Southern Observatory}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{43:1--43:10},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.43},
  URN =		{urn:nbn:de:0030-drops-239041},
  doi =		{10.4230/LIPIcs.CP.2025.43},
  annote =	{Keywords: Modelling, Constraint Programming, Scheduling, SAT, Global Constraints}
}
Document
Invited Talk
DOI: 10.4230/LIPIcs.CP.2024.1
Solving Patience and Solitaire Games with Good Old Fashioned AI (Invited Talk)

Authors: Ian P. Gent

Published in: LIPIcs, Volume 307, 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)

Abstract
While games like Chess, Checkers and Go have been the subject of extensive research in AI for decades, there has been comparatively little study of single player card games. These games are generally called "Patience" in British English and "Solitaire" in US English, and have been popular for hundreds of years and remain so today. In fact, our ignorance of the winnability percentage of just one such game - "Klondike" - has been described as "one of the embarrassments of applied mathematics" by the distinguished statistician Persi Diaconis. I will talk about "Solvitaire", a program to solve patience games given a simple JSON description of the rules of the game and the initial layout. We have used Solvitaire to determine the winnability percentage of dozens different single-player card games with a 95% confidence interval of ± 0.1% or better. For example, we now know the winnability of Klondike as 81.945% ± 0.084% (in the "thoughtful" variant where the player knows the rank and suit of all cards), a 30-fold reduction in confidence interval over the best previous result. The vast majority of results we obtained with Solvitaire are either entirely new or represent significant improvements on previous knowledge. Solvitaire is very much a "Good Old Fashioned AI" approach to solving patience games, without using Machine Learning or Neural networks. It uses exhaustive depth-first search to explore all possible ways that a game could possibly be won, ensuring that games reported unwinnable really are so. This can involve searching extraordinary seach spaces with depths in the millions even including cases where unwinnability is proven. Numerous techniques imported from AI search play an important role in making this search practicable. Particularly important ones are: the use of a transposition tables; the exploitation of symmetry in search; the use of dominances to force certain moves to be made when it is safe to do so; and the use of streamliners. Solvitaire does have some games it performs poorly on, where exhaustive search is unable to prove that no win is possible but an alternative simple proof is in fact available. I will also talk about using constraint models do this, leading to slight improvements in some variants of Klondike but dramatic improvements in others. This talk will include personal anecdotes, explaining for example why it is dedicated to my mother Margaret Gent (1923-2021) for her patience in teaching me to love the game of patience.
Cite as

Ian P. Gent. Solving Patience and Solitaire Games with Good Old Fashioned AI (Invited Talk). In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, p. 1:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{gent:LIPIcs.CP.2024.1,
  author =	{Gent, Ian P.},
  title =	{{Solving Patience and Solitaire Games with Good Old Fashioned AI}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{1:1--1:1},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-336-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{307},
  editor =	{Shaw, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2024.1},
  URN =		{urn:nbn:de:0030-drops-206863},
  doi =		{10.4230/LIPIcs.CP.2024.1},
  annote =	{Keywords: AI Search, Solitaire and Patience Games}
}
Document
DOI: 10.4230/LIPIcs.CP.2022.38
Selecting SAT Encodings for Pseudo-Boolean and Linear Integer Constraints

Authors: Felix Ulrich-Oltean, Peter Nightingale, and James Alfred Walker

Published in: LIPIcs, Volume 235, 28th International Conference on Principles and Practice of Constraint Programming (CP 2022)

Abstract
Many constraint satisfaction and optimisation problems can be solved effectively by encoding them as instances of the Boolean Satisfiability problem (SAT). However, even the simplest types of constraints have many encodings in the literature with widely varying performance, and the problem of selecting suitable encodings for a given problem instance is not trivial. We explore the problem of selecting encodings for pseudo-Boolean and linear constraints using a supervised machine learning approach. We show that it is possible to select encodings effectively using a standard set of features for constraint problems; however we obtain better performance with a new set of features specifically designed for the pseudo-Boolean and linear constraints. In fact, we achieve good results when selecting encodings for unseen problem classes. Our results compare favourably to AutoFolio when using the same feature set. We discuss the relative importance of instance features to the task of selecting the best encodings, and compare several variations of the machine learning method.
Cite as

Felix Ulrich-Oltean, Peter Nightingale, and James Alfred Walker. Selecting SAT Encodings for Pseudo-Boolean and Linear Integer Constraints. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 38:1-38:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{ulricholtean_et_al:LIPIcs.CP.2022.38,
  author =	{Ulrich-Oltean, Felix and Nightingale, Peter and Walker, James Alfred},
  title =	{{Selecting SAT Encodings for Pseudo-Boolean and Linear Integer Constraints}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{38:1--38:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-240-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{235},
  editor =	{Solnon, Christine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.38},
  URN =		{urn:nbn:de:0030-drops-166670},
  doi =		{10.4230/LIPIcs.CP.2022.38},
  annote =	{Keywords: Constraint programming, SAT encodings, machine learning, global constraints, pseudo-Boolean constraints, linear constraints}
}
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