Polynomial calculus for optimization
MaxSAT is the problem of finding an assignment satisfying the maximum number of clauses in a CNF formula. We consider a natural generalization of this problem to generic sets of polynomials and propose a weighted version of Polynomial Calculus to address this problem. Weighted Polynomial Calculus is a natural generalization of the systems MaxSAT-Resolution and weighted Resolution. Unlike such systems, weighted Polynomial Calculus manipulates polynomials with coefficients in a finite field and either weights in N or Z. We show the soundness and completeness of weighted Polynomial Calculus via an algorithmic procedure. Weighted Polynomial Calculus, with weights in N and coefficients in F2, is able to prove efficiently that Tseitin formulas on a connected graph are minimally unsatisfiable. Using weights in Z, it also proves efficiently that the Pigeonhole Principle is minimally unsatisfiable.
Authors
- Marı́a Luisa Bonet (ORCID: https://orcid.org/0000-0003-1646-7177)
- Jordi Levy (ORCID: https://orcid.org/0009-0002-4337-2608)
- Ilario Bonacina (ORCID: https://orcid.org/0000-0002-5697-8070)
Institutions
- Artificial Intelligence Research Institute (ES)
- Universitat Politècnica de Catalunya (ES)
Publication Details
- Journal
- Artificial Intelligence
- Published
- 2024-08-29
- DOI
- https://doi.org/10.1016/j.artint.2024.104208
- Primary Topic
- Formal Methods in Verification
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Simons Institute for the Theory of Computing, University of California Berkeley
- Agencia Estatal de Investigación