Difficulty of Unimodal and Multimodal Landscapes in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{vanneschi:2003:gecco,
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author = "Leonardo Vanneschi and Marco Tomassini and
Manuel Clergue and Philippe Collard",
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title = "Difficulty of Unimodal and Multimodal Landscapes in
Genetic Programming",
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booktitle = "Genetic and Evolutionary Computation -- GECCO-2003",
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editor = "E. Cant{\'u}-Paz and J. A. Foster and K. Deb and
D. Davis and R. Roy and U.-M. O'Reilly and H.-G. Beyer and
R. Standish and G. Kendall and S. Wilson and
M. Harman and J. Wegener and D. Dasgupta and M. A. Potter and
A. C. Schultz and K. Dowsland and N. Jonoska and
J. Miller",
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year = "2003",
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pages = "1788--1799",
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address = "Chicago",
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publisher_address = "Berlin",
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month = "12-16 " # jul,
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volume = "2724",
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series = "LNCS",
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ISBN = "3-540-40603-4",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1007/3-540-45110-2_70",
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abstract = "Fitness distance correlation as a measure of problem
difficulty in genetic programming. A new definition of
distance, called structural distance, is used and
suitable mutation operators for the program space are
defined. The difficulty is studied for a number of
problems, including, for the first time in GP,
multimodal ones, both for the new hand-tailored
mutation operators and standard crossover. Results are
in agreement with empirical observations, thus
confirming that fitness distance correlation can be
considered a reasonable index of difficulty for genetic
programming, at least for the set of problems studied
here.",
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notes = "GECCO-2003. A joint meeting of the twelfth
International Conference on Genetic Algorithms
(ICGA-2003) and the eighth Annual Genetic Programming
Conference (GP-2003)",
- }
Genetic Programming entries for
Leonardo Vanneschi
Marco Tomassini
Manuel Clergue
Philippe Collard
Citations