A developmental model of neural computation using cartesian genetic programming

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@InProceedings{1274022,

• author = "Gul Muhammad Khan and Julian F. Miller and David M. Halliday",
• title = "A developmental model of neural computation using cartesian genetic programming",
• booktitle = "Late breaking paper at Genetic and Evolutionary Computation Conference {(GECCO'2007)}",
• year = "2007",
• month = "7-11 " # jul,
• editor = "Peter A. N. Bosman",
• isbn13 = "978-1-59593-698-1",
• pages = "2535--2542",
• address = "London, United Kingdom",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming, brain",
• URL = "http://gpbib.cs.ucl.ac.uk/gecco2007/docs/p2535.pdf",
• DOI = "doi:10.1145/1274000.1274022",
• publisher = "ACM Press",
• publisher_address = "New York, NY, USA",
• abstract = "The brain has long been seen as a powerful analogy from which novel computational techniques could be devised. However, most artificial neural network approaches have ignored the genetic basis of neural functions. In this paper we describe a radically different approach. We have devised a compartmental model of a neuron as a collection of seven chromosomes encoding distinct computational functions representing aspects of real neurons. This model allows neurons, dendrites, and axon branches to grow, die and change while solving a computational problem. This also causes the synaptic morphology to change and affect the information processing. Since the appropriate computational equivalent functions of neural computation are unknown, we have used a form of genetic programming known as Cartesian Genetic Programming (CGP) to obtain these functions. We have evaluated the learning potential of this system in the context of solving a well known agent based learning scenario, known as wumpus world and obtained promising results.",
• notes = "Distributed on CD-ROM at GECCO-2007 ACM Order No. 910071",

}

Genetic Programming entries for Gul Muhammad Khan Julian F Miller David M Halliday

Citations