GECCO 2011 tutorial

作者: Julian F. Miller , Simon L. Harding

DOI: 10.1145/2001858.2002136

关键词: Arbitrary-precision arithmeticModular designGenetic representationGenetic programmingArtificial neural networkTheoretical computer scienceDirected graphCartesian genetic programmingComputer science

摘要: Cartesian Genetic Programming (CGP) is an increasingly popular and efficient form of that was developed by Julian Miller in 1999 2000. In its classic form, it uses a very simple integer based genetic representation program the directed graph. Graphs are useful representations can be applied to many domains (e.g. electronic circuits, neural networks). number studies, CGP has been shown comparatively other GP techniques. It also program. Since then, classical made more various ways. Notably including automatically defined functions (modular CGP) self-modification operators(self-modifying CGP). SMCGP Miller, Simon Harding Wolfgang Banzhaf. cause evolved programs change themselves as function time. Using this technique possible find general solutions classes problems mathematical algorithms arbitrary parity, n-bit binary addition, sequences provably compute pi e precision, so on). The tutorial will cover basic technique, advanced developments applications variety problem domains.

参考文章(84)
Julian F. Miller, Joseph A. Rothermich, Studying the Emergence of Multicellularity with Cartesian Genetic Programming in Artificial Life. GECCO Late Breaking Papers. pp. 397- 403 ,(2002)
James Alfred Walker, Yang Liu, Gianluca Tempesti, Andy M. Tyrrell, Automatic code generation on a MOVE processor using Cartesian genetic programming international conference on evolvable systems. pp. 238- 249 ,(2010) , 10.1007/978-3-642-15323-5_21
David W. Corne, Peter J. Bentley, CREATIVE EVOLUTIONARY SYSTEMS ,(2001)
Julian F. Miller, An empirical study of the efficiency of learning boolean functions using a Cartesian Genetic Programming approach genetic and evolutionary computation conference. pp. 1135- 1142 ,(1999)
Julian F. Miller, Wolfgang Banzhaf, 15 – Evolving the program for a cell: from French flags to Boolean circuits On Growth, Form and Computers. pp. 278- 301 ,(2003) , 10.1016/B978-012428765-5/50048-7
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Maryam Mahsal Khan, Julian Francis Miller, Gul Muhammad Khan, Evolution of Optimal ANNs for Non-Linear Control Problems using Cartesian Genetic Programming. international conference on artificial intelligence. pp. 339- 346 ,(2010)
Julian F. Miller, Digital filter design at gate-level using evolutionary algorithms genetic and evolutionary computation conference. pp. 1127- 1134 ,(1999)