Abstract
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) capable of acquiring, evolving and re-using partial solutions. In this paper, we apply for the first time CGP and ECGP to the ones-max and order-3 deceptive problems, which are normally associated with Genetic Algorithms. Our approach uses CGP and ECGP to evolve a sequence of commands for a tape-head, which produces an arbitrary length binary string on a piece of tape. Computational effort figures are calculated for CGP and ECGP and our results compare favourably with those of Genetic Algorithms. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Walker, J. A., & Miller, J. F. (2007). Changing the genospace: Solving GA problems with cartesian genetic programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4445 LNCS, pp. 261–270). Springer Verlag. https://doi.org/10.1007/978-3-540-71605-1_24
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