Exploiting Symmetries in MUS Computation

Bleukx, Ignace;Verhaeghe, Hélène;Bogaerts, Bart;Guns, Tias
(2025)

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Authors
  • Bleukx, IgnaceKU Leuven
    Author
  • Author
  • Bogaerts, BartVUB
    Author
  • Guns, TiasKU Leuven
    Author
Abstract
(en) In eXplainable Constraint Solving (XCS), it is common to extract a Minimal Unsatisfiable Subset (MUS) from a set of unsatisfiable constraints. This helps explain to a user why a constraint specification does not admit a solution. Finding MUSes can be computationally expensive for highly symmetric problems, as many combinations of constraints need to be considered. In the traditional context of solving satisfaction problems, symmetry has been well studied, and effective ways to detect and exploit symmetries during the search exist. However, in the setting of finding MUSes of unsatisfiable constraint programs, symmetries are understudied. In this paper, we take inspiration from existing symmetry-handling techniques and adapt well-known MUS-computation methods to exploit symmetries in the specification, speeding-up overall computation time. Our results display a significant reduction of runtime for our adapted algorithms compared to the baseline on symmetric problems.
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Citations

Bleukx, I., Verhaeghe, H., Bogaerts, B., & Guns, T. (2025). Exploiting Symmetries in MUS Computation. Proceedings of the AAAI Conference on Artificial Intelligence, 39(11), 11122-11130. https://doi.org/10.1609/aaai.v39i11.33209 (Original work published 2025)