Elevator Group Supervisory Control System Using Genetic Network Programming with Reinforcement Learning
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{zhou:2005:CEC,
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author = "Jin Zhou and Toru Eguchi and Kotaro Hirasawa and
Jinglu Hu and Sandor Markon",
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title = "Elevator Group Supervisory Control System Using
Genetic Network Programming with Reinforcement
Learning",
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booktitle = "Proceedings of the 2005 IEEE Congress on Evolutionary
Computation",
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year = "2005",
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editor = "David Corne and Zbigniew Michalewicz and
Marco Dorigo and Gusz Eiben and David Fogel and Carlos Fonseca and
Garrison Greenwood and Tan Kay Chen and
Guenther Raidl and Ali Zalzala and Simon Lucas and Ben Paechter and
Jennifier Willies and Juan J. Merelo Guervos and
Eugene Eberbach and Bob McKay and Alastair Channon and
Ashutosh Tiwari and L. Gwenn Volkert and
Dan Ashlock and Marc Schoenauer",
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volume = "1",
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pages = "336--342",
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address = "Edinburgh, UK",
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publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
08855-1331, USA",
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month = "2-5 " # sep,
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organisation = "IEEE Computational Intelligence Society, Institution
of Electrical Engineers (IEE), Evolutionary Programming
Society (EPS)",
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-7803-9363-5",
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DOI = "doi:10.1109/CEC.2005.1554703",
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abstract = "Since Genetic Network Programming (GNP) has been
proposed as a new method of evolutionary computation,
many studies have been done on its applications which
cover not only virtual world problems but also real
world systems like Elevator Group Supervisory Control
System (EGSCS) which is a very large scale stochastic
dynamic optimisation problem. From those researches,
most of the significant features of GNP have been
verified comparing to Genetic Algorithm (GA) and
Genetic Programming (GP). Especially, the improvement
of the performances on EGSCS using GNP showed an
interesting and promising prospect in this field. On
the other hand, some studies based on GNP with
Reinforcement Learning (RL) revealed a better
performance over conventional GNP on some problems such
as tileworld models. As a basic study, Reinforcement
Learning is introduced in this paper expecting to
enhance EGSCS controller using GNP.",
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notes = "CEC2005 - A joint meeting of the IEEE, the IEE, and
the EPS.",
- }
Genetic Programming entries for
Jin Zhou
Toru Eguchi
Kotaro Hirasawa
Jinglu Hu
Sandor Markon
Citations