Evolution of a subsumption architecture that performs a wall following task for an autonomous mobile robot via genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InCollection{Koza:1994:wallGP,

• author = "John R. Koza",
• title = "Evolution of a subsumption architecture that performs a wall following task for an autonomous mobile robot via genetic programming",
• booktitle = "Computational Learning Theory and Natural Learning Systems",
• publisher = "MIT Press",
• year = "1994",
• editor = "Stephen Jose Hanson and Thomas Petsche and Ronald L. Rivest and Michael Kearns",
• volume = "2",
• pages = "321--346",
• address = "Cambridge, MA, USA",
• month = jun,
• ISBN = "0-262-58133-7",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://www.genetic-programming.com/jkpdf/cltnls1994.pdf",
• URL = "http://cognet.mit.edu/book/computational-learning-theory-and-natural-learning-systems-volume-2#chapter19",
• abstract = "The goal in automatic programming is to get a computer to perform a task by telling it what needs to be done, rather than by explicitly programming it. This paper considers the task of automatically generating a computer program to enable an autonomous mobile robot to perform the task of following the wall of an irregular shaped room. A human programmer has written such a program in the style of the subsumption architecture. The solution produced by genetic programming emerges as a result of Darwinian natural selection and genetic crossover (sexual recombination) in a population of computer programs. This evolutionary process is driven by a fitness measure which communicates the nature of the task to the computer.",

}

Genetic Programming entries for John Koza

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