Resolution versus Search: Two Strategies for SAT

  • Authors:

  • Irina Rish;Rina Dechter

  • Affiliations:

  • Information and Computer Science, University of California, Irvine, U.S.A. e-mail: irinar@ics.uci.edu;Information and Computer Science, University of California, Irvine, U.S.A. e-mail: dechter@ics.uci.edu

  • Venue:
  • Journal of Automated Reasoning
  • Year:
  • 2000

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Abstract

The paper compares two popular strategies for solving propositional satisfiability, ibacktracking search and iresolution, and analyzes the complexity of a directional resolution algorithm (DR) as a function of the “width” (iw*) of the problem"s graph. Our empirical evaluation confirms theoretical prediction, showing that on low-iw* problems DR is very efficient, greatly outperforming the backtracking-based Davis–Putnam–Logemann–Loveland procedure (DP). We also emphasize the knowledge-compilation properties of DR and extend it to a tree-clustering algorithm that facilitates query answering. Finally, we propose two hybrid algorithms that combine the advantages of both DR and DP. These algorithms use control parameters that bound the complexity of resolution and allow time/space trade-offs that can be adjusted to the problem structure and to the user"s computational resources. Empirical studies demonstrate the advantages of such hybrid schemes.