Compressing UNSAT Search Trees with Caching

Anthony Blomme; Daniel Le Berre; Anne Parrain; Olivier Roussel

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Paper

Compressing UNSAT Search Trees with Caching

Topics: Explainable Artificial Intelligence

In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, 358-365, 2023 , Lisbon, Portugal

Authors: Anthony Blomme ; Daniel Le Berre ; Anne Parrain and Olivier Roussel

Affiliation: Univ. Artois, CNRS, Centre de Recherche en Informatique de Lens (CRIL), F-62300 Lens, France

Keyword(s): SAT, Explainable AI, Solver.

Abstract: In order to provide users of SAT solvers with small, easily understandable proofs of unsatisfiability, we present caching techniques to identify redundant subproofs and reduce the size of some UNSAT proof trees. In a search tree, we prune branches corresponding to subformulas that were proved unsatisfiable earlier in the tree. To do so, we use a cache inspired by model counters and we adapt it to the case of unsatisfiable formulas. The implementation of this cache in a CDCL and a DPLL solver is discussed. This approach can drastically reduce the UNSAT proof tree of several benchmarks from the SAT’02 and SAT’03 competitions.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Blomme, A. ; Le Berre, D. ; Parrain, A. and Roussel, O. (2023). Compressing UNSAT Search Trees with Caching. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-623-1; ISSN 2184-433X, SciTePress, pages 358-365. DOI: 10.5220/0011671800003393

@conference{icaart23,
author={Anthony Blomme and Daniel {Le Berre} and Anne Parrain and Olivier Roussel},
title={Compressing UNSAT Search Trees with Caching},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2023},
pages={358-365},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011671800003393},
isbn={978-989-758-623-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Compressing UNSAT Search Trees with Caching
SN - 978-989-758-623-1
IS - 2184-433X
AU - Blomme, A.
AU - Le Berre, D.
AU - Parrain, A.
AU - Roussel, O.
PY - 2023
SP - 358
EP - 365
DO - 10.5220/0011671800003393
PB - SciTePress