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.
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Hoang, TH., McKay, R.I.(., Essam, D., Nguyen, X.H. (2008). Learning General Solutions through Multiple Evaluations during Development. In: Hornby, G.S., Sekanina, L., Haddow, P.C. (eds) Evolvable Systems: From Biology to Hardware. ICES 2008. Lecture Notes in Computer Science, vol 5216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85857-7_18
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DOI: https://doi.org/10.1007/978-3-540-85857-7_18
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