Towards generic explanations for pen and paper puzzles with MUSes

Joan Espasa Arxer, Ian P. Gent, Ruth Hoffmann, Christopher Jefferson, Matthew J. McIlree, Alice M. Lynch

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Pen and paper puzzles like Sudoku, Futoshiki and Star Battle are hugely popular. Solving such puzzles can be a trivial task for modern AI systems. However, most AI systems solve problems using a form of backtracking, while people try to avoid backtracking as much as possible. This means that existing AI systems do not output explanations about their reasoning that are meaningful to people. We present Demystify, a tool which allows puzzles to be expressed in a high-level constraint programming language and uses MUSes to allow us to produce descriptions of steps in the puzzle solving. We give several improvements to the existing techniques for solving puzzles with MUSes, which allow us to solve a range of significantly more complex puzzles and give higher quality explanations. We demonstrate the effectiveness and generality of Demystify by comparing its results to documented strategies for solving a range of pen and paper puzzles by hand, showing that our technique can find many of the same explanations.
Original languageEnglish
Title of host publicationProceedings of the SICSA eXplainable Artifical Intelligence Workshop 2021
EditorsKyle Martin, Nirmalie Wiratunga, Anjana Wijekoon
Number of pages8
Publication statusPublished - 2 Jul 2021
EventSICSA eXplainable Artifical Intelligence Workshop - Aberdeen, United Kingdom
Duration: 1 Jun 2021 → …

Publication series

NameCEUR Workshop Proceedings
ISSN (Electronic)1613-0073


WorkshopSICSA eXplainable Artifical Intelligence Workshop
Abbreviated titleSICSA XAI 2021
Country/TerritoryUnited Kingdom
Period1/06/21 → …


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