Abstract
This article describes the similarities between learning classifier systems (LCSs) and coevolutionary algorithm, and exploits these similarities by taking ideas used by LCSs to design a non-generational coevolutionary algorithm that incrementally estimates fitness of individuals. The algorithm solves some of the problems known to exist in coevolutionary algorithms: it does not loose gradient and is successful in generating an arms race. It is tested on MAX 3-SAT problems, and compared to a generational coevolutionary algorithm and a simple genetic algorithm.
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Palacios-Durazo, R.A., Valenzuela-Rendón, M. (2004). Similarities Between Co-evolution and Learning Classifier Systems and Their Applications. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24854-5_58
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DOI: https://doi.org/10.1007/978-3-540-24854-5_58
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