Co-Evolving Fuzzy Decision Trees and Scenarios
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{smith:2008:cec,
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author = "James F. {Smith, III}",
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title = "Co-Evolving Fuzzy Decision Trees and Scenarios",
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booktitle = "2008 IEEE World Congress on Computational
Intelligence",
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year = "2008",
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editor = "Jun Wang",
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pages = "3167--3176",
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address = "Hong Kong",
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month = "1-6 " # jun,
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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isbn13 = "978-1-4244-1823-7",
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file = "EC0700.pdf",
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DOI = "doi:10.1109/CEC.2008.4631227",
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abstract = "A co-evolutionary data mining algorithm has been
invented that automatically generates decision logic in
the form of fuzzy decision trees (FDTs). The algorithm
initially uses a genetic program (GP) to mine a
database of scenarios to automatically create the fuzzy
logic. This is followed by the application of a genetic
algorithm (GA) that is used to search for pathological
scenarios (PS) that result in unsatisfactory
performance by the fuzzy logic found by the GP. The
fuzzy logic found in the previous step by the GP along
with failure criteria (FC) is used to form the fitness
function for the GA. If the GA fails to find
pathological scenarios then the co-evolution ends;
otherwise, the new scenarios are appended to the GP's
database followed by GP based data mining and a GA
scenario search. A detailed description of the
co-evolution of a fuzzy decision tree for real-time
control of unmanned air vehicles is provided. The
fitness functions for the GP, terminal set, function
set, and methods of accelerating convergence are
included. The fitness function for the GA and a method
of representing scenarios as chromosomes are given.
Simulations related to validation of the fuzzy logic
are discussed.",
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keywords = "genetic algorithms, genetic programming",
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notes = "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
EPS and the IET.",
- }
Genetic Programming entries for
James F Smith III
Citations