Generation of hard non-clausal random satisfiability problems

  • Authors:
  • Juan A. Navarro;Andrei Voronkov

  • Affiliations:
  • The University of Manchester, School of Computer Science;The University of Manchester, School of Computer Science

  • Venue:
  • AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
  • Year:
  • 2005

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Abstract

We present the results from experiments with a new family of random formulas for the satisfiability problem. Our proposal is a generalisation of the random k-SAT model that introduces non-clausal formulas and exhibits interesting features such as experimentally observed sharp phase transition and the easy-hard-easy pattern. The experimental results provide some insights on how the use of different clausal translations can affect the performance of satisfiability solving algorithms. We also expect our model to provide diverse and challenging benchmarks for developers of SAT procedures for non-clausal formulas.