This paper studies the characteristics of interaction among genetic evolution, individual learning and social learning using an evolutionary computation system with NK fitness landscape, both under static and dynamic environments. We show conditions for effective social learning: at least 1.5 times lighter cost of social learning than that of individual learning, beneficial teaching action, low epistasis and dynamic environment. © 2008 Springer Berlin Heidelberg.
CITATION STYLE
Hashimoto, T., & Warashina, K. (2008). Evolutionary computation using interaction among genetic evolution, individual learning and social learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5351 LNAI, pp. 152–163). https://doi.org/10.1007/978-3-540-89197-0_17
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