By the same authors

Changing the genospace: Solving GA problems with Cartesian Genetic Programming

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Author(s)

Department/unit(s)

Publication details

Title of host publicationGenetic Programming, Proceedings
DatePublished - 2007
Pages261-270
Number of pages10
PublisherSPRINGER-VERLAG BERLIN
Place of PublicationBERLIN
EditorsM ONeill, A Ekart, L Vanneschi, AI EsparciaAlcazar
Original languageEnglish
ISBN (Print)978-3-540-71602-0

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.

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations