Rapid Training of Thermal Agents with Single Parent Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{ashlock:2005:CECd,
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author = "Daniel A. Ashlock and Kenneth M. Bryden and
Wendy Ashlock and Stephen P. Gent",
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title = "Rapid Training of Thermal Agents with Single Parent
Genetic Programming",
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booktitle = "Proceedings of the 2005 IEEE Congress on Evolutionary
Computation",
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year = "2005",
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editor = "David Corne and Zbigniew Michalewicz and
Marco Dorigo and Gusz Eiben and David Fogel and Carlos Fonseca and
Garrison Greenwood and Tan Kay Chen and
Guenther Raidl and Ali Zalzala and Simon Lucas and Ben Paechter and
Jennifier Willies and Juan J. Merelo Guervos and
Eugene Eberbach and Bob McKay and Alastair Channon and
Ashutosh Tiwari and L. Gwenn Volkert and
Dan Ashlock and Marc Schoenauer",
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volume = "3",
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pages = "2122--2129",
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address = "Edinburgh, UK",
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publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
08855-1331, USA",
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month = "2-5 " # sep,
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organisation = "IEEE Computational Intelligence Society, Institution
of Electrical Engineers (IEE), Evolutionary Programming
Society (EPS)",
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-7803-9363-5",
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DOI = "doi:10.1109/CEC.2005.1554957",
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size = "8 pages",
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abstract = "The temperature profile across an object can be
computed by iterative methods. The time spent waiting
for iterative solutions to converge for multiple
objects in a complex configuration is an impediment to
exploratory analysis of engineering systems. A
high-quality rapidly computed initial guess can speed
convergence for an iterative algorithm. A system is
described and tested for creating thermal agents that
supply such initial guesses. Thermal agents are
specific to an object but general across different
thermal boundary conditions. During an off-line
training phase, genetic programming is used to locate a
thermal agent by training on several sets of boundary
conditions. In use, thermal agents transform boundary
conditions into rapidly-converged initial values on a
cellular decomposition of an object. the impact of
using single parent genetic programming on thermal
agents is tested. Single parent genetic programming
replaces the usual sub-tree crossover in genetic
programming with crossover with members of an
unchanging ancestor set. The use of this ancestor set
permits the incorporation of expert knowledge into the
system as well as permitting the re-use of solutions
derived on one object to speed training of thermal
agents for another object. For three types of
experiments, incorporating expert knowledge; re-using
evolved solutions; and transferring knowledge between
distinct configurations statistically significant
improvements are obtained with single parent
techniques.",
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notes = "CEC2005 - A joint meeting of the IEEE, the IEE, and
the EPS.",
- }
Genetic Programming entries for
Daniel Ashlock
Kenneth M Bryden
Wendy Ashlock
Stephen P Gent
Citations