Evolution of Robot Controller Using Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{eurogp:HardingM05,

• author = "Simon Harding and Julian F. Miller",
• editor = "Maarten Keijzer and Andrea Tettamanzi and Pierre Collet and Jano I. {van Hemert} and Marco Tomassini",
• title = "Evolution of Robot Controller Using Cartesian Genetic Programming",
• booktitle = "Proceedings of the 8th European Conference on Genetic Programming",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "3447",
• year = "2005",
• address = "Lausanne, Switzerland",
• month = "30 " # mar # " - 1 " # apr,
• organisation = "EvoNet",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming",
• ISBN = "3-540-25436-6",
• pages = "62--73",
• DOI = "doi:10.1007/978-3-540-31989-4_6",
• DOI = "doi:10.1007/b107383",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• abstract = "Cartesian Genetic Programming is a graph based representation that has many benefits over traditional tree based methods, including bloat free evolution and faster evolution through neutral search. Here, an integer based version of the representation is applied to a traditional problem in the field : evolving an obstacle avoiding robot controller. The technique is used to rapidly evolve controllers that work in a complex environment and with a challenging robot design. The generalisation of the robot controllers in different environments is also demonstrated. A novel fitness function based on chemical gradients is presented as a means of improving evolvability in such tasks.",
• notes = "Part of \cite{keijzer:2005:GP} EuroGP'2005 held in conjunction with EvoCOP2005 and EvoWorkshops2005",

}

Genetic Programming entries for Simon Harding Julian F Miller

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