Abstract
Co-evolutionary algorithms are evolutionary algorithms in which the given individual’s fitness value estimation is made on the basis of interactions of this individual with other individuals present in the population. In this paper agent-based versions of co-operative co-evolutionary algorithms are presented and evaluated with the use of standard multi-objective test functions. The results of experiments are used to compare proposed agent-based co-evolutionary algorithms with state-of-the-art multi-objective evolutionary algorithms: SPEA2 and NSGA-II.
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Dreżewski, R., Obrocki, K. (2009). Co-operative Co-evolutionary Approach to Multi-objective Optimization. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds) Hybrid Artificial Intelligence Systems. HAIS 2009. Lecture Notes in Computer Science(), vol 5572. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02319-4_33
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DOI: https://doi.org/10.1007/978-3-642-02319-4_33
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