Instance-Based Selection of Policies for SAT Solvers

Execution of most of the modern DPLL-based SAT solvers is guided by a number of heuristics. Decisions made during the search process are usually driven by some fixed heuristic policies. Despite the outstanding progress in SAT solving in recent years, there is still an appealing lack of techniques for selecting policies appropriate for solving specific input formulae. In this paper we present a methodology for instancebased selection of solver’s policies that uses a data-mining classification technique. The methodology also relies on analysis of relationships between formulae, their families, and their suitable solving strategies. The evaluation results are very good, demonstrate practical usability of the methodology, and encourage further efforts in this direction.

• Type: Conference
• Year: 2009
• Where: SAT
• Authors: Mladen Nikolic, Filip Maric, Predrag Janicic
• Keywords: DPLL-based SAT Solvers, SAT 2009, Specific Input Formulae, Suitable Solving Strategies