2013
Local Search and Restart Strategies for Satisfiability Solving in Fuzzy Logics
Publication
Publication
Presented at the
IEEE Symposium Series on Computational Intelligence
Satisfiability solving in fuzzy logics is a subject that has not been researched much, certainly compared to satisfiability in propositional logics. Yet, fuzzy logics are a powerful tool for modelling complex problems. Recently, we proposed an optimization approach to solving satisfiability in fuzzy logics and compared the standard Covariance Matrix Adaptation Evolution Strategy algorithm (CMA-ES) with an analytical solver on a set of benchmark problems. Especially on more finegrained problems did CMA-ES compare favourably to the analytical approach. In this paper, we evaluate two types of hillclimber in addition to CMA-ES, as well as restart strategies for these algorithms. Our results show that a population-based hillclimber outperforms CMA-ES on the harder problem class.
| Additional Metadata | |
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| IEEE | |
| R. Alcalá , Y. Nojima | |
| doi.org/10.1109/GEFS.2013.6601055 | |
| IEEE Symposium Series on Computational Intelligence | |
| Organisation | Intelligent and autonomous systems |
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Brys, T., Drugan, M. M., Bosman, P., de Cock, M., & Nowé, A. (2013). Local Search and Restart Strategies for Satisfiability Solving in Fuzzy Logics. In R. Alcalá & Y. Nojima (Eds.), Proceedings of IEEE Symposium Series on Computational Intelligence 2013 (pp. 52–59). IEEE. doi:10.1109/GEFS.2013.6601055 |
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