A developmental model of neural computation using cartesian genetic programming
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- @InProceedings{1274022,
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author = "Gul Muhammad Khan and Julian F. Miller and
David M. Halliday",
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title = "A developmental model of neural computation using
cartesian genetic programming",
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booktitle = "Late breaking paper at Genetic and Evolutionary
Computation Conference {(GECCO'2007)}",
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year = "2007",
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month = "7-11 " # jul,
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editor = "Peter A. N. Bosman",
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isbn13 = "978-1-59593-698-1",
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pages = "2535--2542",
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address = "London, United Kingdom",
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keywords = "genetic algorithms, genetic programming, cartesian
genetic programming, brain",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco2007/docs/p2535.pdf",
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DOI = "doi:10.1145/1274000.1274022",
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publisher = "ACM Press",
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publisher_address = "New York, NY, USA",
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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.",
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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