Analysis of Semantic Modularity for Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Krawiec:2009:FCDS,
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author = "Krzysztof Krawiec and Bartosz Wieloch",
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title = "Analysis of Semantic Modularity for Genetic
Programming",
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journal = "Foundations of Computing and Decision Sciences",
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year = "2009",
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volume = "34",
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number = "4",
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pages = "265--285",
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publisher = "Poznan University of Technology",
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keywords = "genetic algorithms, genetic programming, semantics,
modularity, problem decomposition",
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ISSN = "0867-6356",
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URL = "http://fcds.cs.put.poznan.pl/FCDS/ArticleDetails.aspx?articleId=219",
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broken = "http://fcds.cs.put.poznan.pl/FCDS2/ArticleDetails.aspx?articleId=219",
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size = "21 pages",
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abstract = "In this paper we analyze the properties of functional
modularity, a concept introduced in
\cite{DBLP:conf/gecco/KrawiecW09} for detecting and
measuring modularity in problems of automatic program
synthesis, in particular by means of genetic
programming. The basic components of functional
modularity approach are subgoals -- entities that
embody module's semantic -- and monotonicity, a measure
for assessing subgoals' potential utility for searching
for good modules. For a given subgoal and a sample of
solutions decomposed into parts and contexts according
to module definition, monotonicity measures the
correlation of distance between semantics of solution's
part and the fitness of the solution. The central tenet
of this approach is that highly monotonous subgoals can
be used to decompose the task and improve search
convergence. In the experimental part we investigate
the properties of functional modularity using eight
instances of problems of Boolean function synthesis.
The results show that monotonicity varies depending on
problem's structure of modularity and correctly
identifies good subgoals, potentially enabling
automatic program decomposition.",
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notes = "http://fcds.cs.put.poznan.pl/fcds/",
- }
Genetic Programming entries for
Krzysztof Krawiec
Bartosz Wieloch
Citations