Genetic Network Programming with generalized rule accumulation
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- @InProceedings{Wang:2010:cec,
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author = "Lutao Wang and Shingo Mabu and Qingbiao Meng and
Kotaro Hirasawa",
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title = "Genetic Network Programming with generalized rule
accumulation",
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booktitle = "IEEE Congress on Evolutionary Computation (CEC 2010)",
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year = "2010",
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address = "Barcelona, Spain",
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month = "18-23 " # jul,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming, Genetic
Network Programming",
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isbn13 = "978-1-4244-6910-9",
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abstract = "Genetic Network Programming(GNP) is a newly developed
evolutionary computation method using a directed graph
as its gene structure, which is its unique feature. It
is competent for dealing with complex problems in
dynamic environments and is now being well studied and
applied to many real-world problems such as: elevator
supervisory control, stock price prediction, traffic
volume forecast and data mining, etc. This paper
proposes a new method to accumulate evolutionary
experiences and guide agent's actions by extracting and
using generalised rules. Each generalized rule is a
state-action chain which contains the past information
and the current information. These generalised rules
are accumulated and updated in the evolutionary period
and stored in the rule pool which serves as an
experience set for guiding new agent's actions. We
designed a two-stage architecture for the proposed
method and applied it to the Tile-world problem, which
is an excellent benchmark for multi-agent systems. The
simulation results demonstrated the efficiency and
effectiveness of the proposed method in terms of both
generalisation ability and average fitness values and
showed that the generalised rule accumulation method is
especially remarkable when dealing with non-Markov
problems.",
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DOI = "doi:10.1109/CEC.2010.5586284",
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notes = "WCCI 2010. Also known as \cite{5586284}",
- }
Genetic Programming entries for
Lutao Wang
Shingo Mabu
QingBiao Meng
Kotaro Hirasawa
Citations