Multiobjective GP for Human-Understandable Models: A Practical Application
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InCollection{Rodriguez-Vazquez:2008:MPSN,
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author = "Katya Rodriguez-Vazquez and Peter J. Fleming",
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title = "Multiobjective GP for Human-Understandable Models: A
Practical Application",
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booktitle = "Multiobjective Problem Solving from Nature: from
concepts to applications",
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publisher = "Springer",
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year = "2008",
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editor = "Joshua Knowles and David Corne and Kalyanmoy Deb",
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series = "Natural Computing",
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chapter = "10",
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pages = "201--218",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-540-72963-1",
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DOI = "doi:10.1007/978-3-540-72964-8_10",
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abstract = "The work presented in this chapter is concerned with
the identification and modelling of nonlinear dynamical
systems using multiobjective evolutionary algorithms
(MOEAs). This problem involves the processes of
structure selection, parameter estimation, model
performance and model validation and defines a complex
solution space. Evolutionary algorithms (EAs), in
particular genetic programming (GP), are found to
provide a way of evolving models to solve this
identification and modelling problem, and their use is
extended to encompass multiobjective functions.
Multiobjective genetic programming (MOGP) is then
applied to multiple conflicting objectives in order to
yield a set of simple and valid human-understandable
models which can reproduce the behaviour of a given
unknown system.",
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notes = "http://www.springer.com/west/home/computer/artificial?SGWID=4-147-22-173745027-0",
- }
Genetic Programming entries for
Katya Rodriguez-Vazquez
Peter J Fleming
Citations