Abstract
In this paper, we investigate whether performing multiple evaluations during development - a technique we call Evolutionary Developmental Evaluation (EDE) - could help developmental Genetic Programming (GP) evolve general solutions, solving not only the original (training) problem, but also unseen similar problems (with higher degrees of complexity). The hypothesis is tested on two families of regression problems, and the experimental results support the hypothesis. © 2008 Springer-Verlag Berlin Heidelberg.
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Hoang, T. H., McKay, R. I., Essam, D., & Nguyen, X. H. (2008). Learning general solutions through multiple evaluations during development. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5216 LNCS, pp. 201–212). Springer Verlag. https://doi.org/10.1007/978-3-540-85857-7_18
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