Proving Unsatisfiability of CNFs Locally

We introduce a new method for checking satisfiability of conjunctive normal forms (CNFs). The method is based on the fact that if no clause of a CNF contains a satisfying assignment in its 1-neighborhood, then this CNF is unsatisfiable. (The 1-neighborhood of a clause is the set of all assignments satisfying only one literal of this clause.) The idea of 1-neighborhood exploration allows one to prove unsatisfiability without generating an empty clause. The reason for avoiding the generation of an empty clause is that we believe that no deterministic algorithm can efficiently reach a global goal (deducing an empty clause) using an inherently local operation (resolution). At the same time, when using 1-neighborhood exploration, a global goal is replaced with a set of local subgoals, which makes it possible to optimize steps of the proof. We introduce two proof systems formalizing 1-neighborhood exploration. An interesting open question is whether there exists a class of CNFs for which the introduced systems have proofs that are exponentially shorter than the ones that can be obtained by general resolution.

[1]  Maria Luisa Bonet,et al.  Exponential separations between restricted resolution and cutting planes proof systems , 1998, Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280).

[2]  Alasdair Urquhart,et al.  Formal Languages]: Mathematical Logic--mechanical theorem proving , 2022 .

[3]  Armin Haken,et al.  The Intractability of Resolution , 1985, Theor. Comput. Sci..

[4]  Bart Selman,et al.  Noise Strategies for Improving Local Search , 1994, AAAI.

[5]  Eli Ben-Sasson,et al.  Near Optimal Separation Of Tree-Like And General Resolution , 2004, Comb..

[6]  Matthew L. Ginsberg,et al.  Dynamic Backtracking , 1993, J. Artif. Intell. Res..

[7]  Henry Kautz,et al.  Noise Strategies for Local Search , 1994, AAAI 1994.

[8]  Hector J. Levesque,et al.  Hard and Easy Distributions of SAT Problems , 1992, AAAI.

[9]  Hector J. Levesque,et al.  A New Method for Solving Hard Satisfiability Problems , 1992, AAAI.

[10]  Donald W. Loveland,et al.  A machine program for theorem-proving , 2011, CACM.

[11]  Endre Szemerédi,et al.  Many hard examples for resolution , 1988, JACM.

[12]  J. A. Robinson,et al.  A Machine-Oriented Logic Based on the Resolution Principle , 1965, JACM.

[13]  Armin Haken The intractability of resolution (complexity) , 1984 .

[14]  Karem A. Sakallah,et al.  GRASP—a new search algorithm for satisfiability , 1996, ICCAD 1996.

[15]  Hilary Putnam,et al.  A Computing Procedure for Quantification Theory , 1960, JACM.

[16]  Zvi Galil,et al.  On the validity and complexity of bounded resolution , 1975, STOC.

[17]  Bart Selman,et al.  Ten Challenges in Propositional Reasoning and Search , 1997, IJCAI.

[18]  Joao Marques-Silva,et al.  GRASP-A new search algorithm for satisfiability , 1996, Proceedings of International Conference on Computer Aided Design.