Preliminary Study of Bloat in Genetic Programming with Behavior-Based Search
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Trujillo:2013:EVOLVE,
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author = "Leonardo Trujillo and Enrique Naredo and
Yuliana Martinez",
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title = "Preliminary Study of Bloat in Genetic Programming with
Behavior-Based Search",
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booktitle = "EVOLVE - A Bridge between Probability, Set Oriented
Numerics, and Evolutionary Computation IV",
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year = "2013",
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editor = "Michael Emmerich and Andre Deutz and
Oliver Schuetze and Thomas Baeck and Emilia Tantar and
Alexandru-Adrian and Pierre {Del Moral} and Pierrick Legrand and
Pascal Bouvry and Carlos A. Coello",
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volume = "227",
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series = "Advances in Intelligent Systems and Computing",
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pages = "293--305",
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address = "Leiden, Holland",
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month = jul # " 10-13",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Bloat,
Novelty Search",
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isbn13 = "978-3-319-01127-1",
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DOI = "doi:10.1007/978-3-319-01128-8_19",
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abstract = "Bloat is one of the most interesting theoretical
problems in genetic programming (GP), and one of the
most important pragmatic limitations in the development
of real-world GP solutions. Over the years, many
theories regarding the causes of bloat have been
proposed and a variety of bloat control methods have
been developed. It seems that one of the underlying
causes of bloat is the search for fitness; as the
fitness-causes-bloat theory states, selective bias
towards fitness seems to unavoidably lead the search
towards programs with a large size. Intuitively,
however, abandoning fitness does not appear to be an
option. This paper, studies a GP system that does not
require an explicit fitness function, instead it relies
on behavior-based search, where programs are described
by the behavior they exhibit and selective pressure is
biased towards unique behaviours using the novelty
search algorithm. Initial results are encouraging, the
average program size of the evolving population does
not increase with novelty search; i.e., bloat is
avoided by focusing on novelty instead of quality.",
- }
Genetic Programming entries for
Leonardo Trujillo
Enrique Naredo
Yuliana Martinez
Citations