Rule Accumulation Method Based on Credit Genetic Network Programming
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gp-bibliography.bib Revision:1.7964
- @InProceedings{Wang:2012:CECd,
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title = "Rule Accumulation Method Based on Credit Genetic
Network Programming",
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author = "Lutao Wang and Wei Xu and Shingo Mabu and
Kotaro Hirasawa",
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pages = "3651--3658",
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booktitle = "Proceedings of the 2012 IEEE Congress on Evolutionary
Computation",
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year = "2012",
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editor = "Xiaodong Li",
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month = "10-15 " # jun,
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DOI = "doi:10.1109/CEC.2012.6253004",
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address = "Brisbane, Australia",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, Evolutionary
games and multi-agent systems, Evolutionary
simulation-based optimization, Intelligent systems
applications, Genetic Network Programming",
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abstract = "As a new promising evolutionary computation method,
Genetic Network Programming (GNP) is good at generating
action rules for multi-agent control in dynamic
environments. However, some unimportant nodes exist in
the program of GNP. These nodes serve as some redundant
information which decreases the performance of GNP and
the quality of the generated rules. In order to prune
these nodes, this paper proposes a novel method named
Credit GNP, where a credit branch is added to each
node. When the credit branch is visited, the node is
neglected and its function is not executed, so that the
unimportant nodes could be jumped. The probability of
visiting this credit branch and to which node it is
jumped is determined by both evolution and
Sarsa-learning, therefore, the unimportant nodes could
be pruned automatically. Simulation results on the
Tile-world problem show that the proposed method could
get better programs and generate better and more
general rules.",
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notes = "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the
EPS and the IET.",
- }
Genetic Programming entries for
Lutao Wang
Wei Xu
Shingo Mabu
Kotaro Hirasawa
Citations