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On synergistic interactions between evolution, development and layered learning

Hoang, T.-H. and McKay, R.I. and Essam, D. and Hoai, N.X. (2011) On synergistic interactions between evolution, development and layered learning. IEEE Transactions on Evolutionary Computation, 15 (3): 5898401. pp. 287-312. ISSN 1089778X

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Abstract

We investigate interactions between evolution, development and lifelong layered learning in a combination we call evolutionary developmental evaluation (EDE), using a specific implementation, developmental tree-adjoining grammar guided genetic programming (GP). The approach is consistent with the process of biological evolution and development in higher animals and plants, and is justifiable from the perspective of learning theory. In experiments, the combination is synergistic, outperforming algorithms using only some of these mechanisms. It is able to solve GP problems that lie well beyond the scaling capabilities of standard GP. The solutions it finds are simple, succinct, and highly structured. We conclude this paper with a number of proposals for further extension of EDE systems. © 2011 IEEE.

Item Type: Article
Divisions: Faculties > Faculty of Information Technology
Identification Number: 10.1109/TEVC.2011.2150752
Uncontrolled Keywords: Developmental; evaluation; incremental evolution; Layered learning; modularity; regularity; structural; Animals; Genetic algorithms; Genetic programming
Additional Information: Language of original document: English.
URI: http://eprints.lqdtu.edu.vn/id/eprint/10152

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