Accelerating SAT Solving by Common Subclause Elimination
DOI:
https://doi.org/10.1609/aaai.v29i1.9732Abstract
Boolean SATisfiability (SAT) is an important problem in AI. SAT solvers have been effectively used in important industrial applications including automated planning and verification. In this paper, we present novel algorithms for fast SAT solving by employing two common subclause elimination (CSE) approaches. Our motivation is that modern SAT solving techniques can be more efficient on CSE-processed instances. Empirical study shows that CSE can significantly speed up SAT solving.
Downloads
Published
2015-03-04
How to Cite
Yan, Y., Gutierrez, C., Jn-Charles, J., Bao, F., & Zhang, Y. (2015). Accelerating SAT Solving by Common Subclause Elimination. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9732
Issue
Section
Student Abstract Track