Understand Restart of SAT Solver Using Search Similarity Index (Student Abstract)
DOI:
https://doi.org/10.1609/aaai.v37i13.26978Keywords:
SAT Problem, SAT Solver, Restart, Similarity Of SearchAbstract
SAT solvers are widely used to solve many industrial problems because of their high performance, which is achieved by various heuristic methods. Understanding why these methods are effective is essential to improving them. One approach to this is analyzing them using qualitative measurements. In our previous study, we proposed search similarity index (SSI), a metric to quantify the similarity between searches. SSI significantly improved the performance of the parallel SAT solver. Here, we apply SSI to analyze the effect of restart, a key SAT solver technique. Experiments using SSI reveal the correlation between the difficulty of instances and the search change effect by restart, and the reason behind the effectiveness of the state-of-the-art restart method is also explained.Downloads
Published
2023-09-06
How to Cite
Iida, Y., Sonobe, T., & Inaba, M. (2023). Understand Restart of SAT Solver Using Search Similarity Index (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16236-16237. https://doi.org/10.1609/aaai.v37i13.26978
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Section
AAAI Student Abstract and Poster Program