Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{Kodjabachian:1998:ieeeTNN,

• author = "Jerome Kodjabachian and Jean-Arcady Meyer",
• title = "Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects",
• journal = "IEEE Transactions on Neural Networks",
• year = "1998",
• volume = "9",
• number = "5",
• pages = "796--812",
• month = sep,
• keywords = "genetic algorithms, genetic programming, animats, leaky integrators, recurrent neural networks, sgoce paradigm, developmental grammar",
• ISSN = "1045-9227",
• DOI = "doi:10.1109/72.712153",
• size = "17 pages",
• abstract = "This paper describes how the SGOCE paradigm has been used to evolve developmental programs capable of generating recurrent neural networks that control the behaviour of simulated insects. This paradigm is characterised by an encoding scheme, an evolutionary algorithm, syntactic constraints, and an incremental strategy that are described in turn. The additional use of an insect model equipped with six legs and two antennae made it possible to generate control modules that allowed it to successively add gradient-following and obstacle-avoidance capacities to walking behaviour. The advantages of this evolutionary approach, together with directions for future work, are discussed",
• notes = "also known as \cite{712153}",

}

Genetic Programming entries for Jerome Kodjabachian Jean-Arcady Meyer

Citations