A Variable Size Mechanism of Distributed Graph Programs for Creating Agent Behaviors
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Mabu:2013:CEC,
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article_id = "1137",
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author = "Shingo Mabu and Kotaro Hirasawa and
Masanao Obayashi and Takashi Kuremoto",
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title = "A Variable Size Mechanism of Distributed Graph
Programs for Creating Agent Behaviors",
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booktitle = "2013 IEEE Conference on Evolutionary Computation",
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volume = "1",
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year = "2013",
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month = jun # " 20-23",
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editor = "Luis Gerardo {de la Fraga}",
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pages = "1756--1762",
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address = "Cancun, Mexico",
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keywords = "genetic algorithms, genetic programming, GNP",
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isbn13 = "978-1-4799-0453-2",
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DOI = "doi:10.1109/CEC.2013.6557773",
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size = "7 pages",
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abstract = "Genetic Algorithm (GA) and Genetic Programming (GP)
are typical evolutionary algorithms using string and
tree structures, respectively, and there have been many
studies on the extension of GA and GP. How to represent
solutions, e.g., strings, trees, graphs, etc., is one
of the important research topics and Genetic Network
Programming (GNP) has been proposed as one of the
graph-based evolutionary algorithms. GNP represents its
solutions using directed graph structures and has been
applied to many applications. However, when GNP is
applied to complex real world systems, large size of
the programs is needed to represent various kinds of
control rules. In this case, the efficiency of
evolution and the performance of the systems may
decrease due to its huge structures. Therefore,
distributed GNP has been studied based on the idea of
divide and conquer, where the programs are divided into
several subprograms and they cooperatively control
whole tasks. However, because the previous work divided
a program into some subprograms with the same size, it
cannot adjust the sizes of the subprograms depending on
the problems. Therefore, in this paper, an efficient
evolutionary algorithm of variable size distributed GNP
is proposed and its performance is evaluated by the
tileworld problem that is one of the benchmark problems
of multiagent systems in dynamic environments.",
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notes = "CEC 2013 - A joint meeting of the IEEE, the EPS and
the IET.",
- }
Genetic Programming entries for
Shingo Mabu
Kotaro Hirasawa
Masanao Obayashi
Takashi Kuremoto
Citations