A novel approach of solving the CNF-SAT problem
Xili Wang

TL;DR
This paper compares two algorithms, PL-Resolution and WalkSAT, for solving the NP-Complete CNF-SAT problem, highlighting their differences in certainty, speed, and practicality.
Contribution
It provides an analysis of the performance and trade-offs between a complete algorithm and a faster, incomplete heuristic for CNF-SAT.
Findings
PL-Resolution is sound and complete for CNF-SAT.
WalkSAT is faster but not guaranteed to find a solution.
WalkSAT performs acceptably on easier problems.
Abstract
In this paper, we discussed CNF-SAT problem (NP-Complete problem) and analysis two solutions that can solve the problem, the PL-Resolution algorithm and the WalkSAT algorithm. PL-Resolution is a sound and complete algorithm that can be used to determine satisfiability and unsatisfiability with certainty. WalkSAT can determine satisfiability if it finds a model, but it cannot guarantee to find a model even there exists one. However, WalkSAT is much faster than PL-Resolution, which makes WalkSAT more practical; and we have analysis the performance between these two algorithms, and the performance of WalkSAT is acceptable if the problem is not so hard.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsConstraint Satisfaction and Optimization · Logic, programming, and type systems · AI-based Problem Solving and Planning
