Analysis Of Robustness Of Robot Programs Generated By Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{oai:CiteSeerPSU:511796,
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title = "Analysis Of Robustness Of Robot Programs Generated By
Genetic Programming",
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author = "Roongroj Nopsuwanchai and Prabhas Chongstitvatana",
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booktitle = "First Asian Sympoium on Industrial Automation and
Robotics BITEC",
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year = "1999",
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address = "Bangkok, Thailand",
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month = "6-7 " # may,
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keywords = "genetic algorithms, genetic programming",
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citeseer-isreferencedby = "oai:CiteSeerPSU:81384",
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annote = "The Pennsylvania State University CiteSeer Archives",
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language = "en",
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oai = "oai:CiteSeerPSU:511796",
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rights = "unrestricted",
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URL = "http://citeseer.ist.psu.edu/cache/papers/cs/20674/http:zSzzSzwww.cp.eng.chula.ac.thzSzfacultyzSzpjwzSzpaperzSznopsuwanchai.pdf/nopsuwanchai99analysis.pdf",
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URL = "http://citeseer.ist.psu.edu/511796.html",
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size = "5 pages",
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abstract = "The robot programs generated by Genetic Programming
(GP) are found to be 'brittle', i.e. they fail to work
when the environment is changed. Perturbation has been
used to improve robustness. By introducing perturbation
during the evolution of robot programs, the robustness
of robot programs can be improved. This paper analyses
the cause of the difference of robustness between robot
programs using the case of robot navigation problems.
The analysis is based on the notion of 'trace' of
execution. The result of the analysis shows that the
robustness of robot programs depends on the reuse of
the 'experience' that a robot program acquired during
evolution. To improve robustness, the size of the set
of 'experience' should be increased and/or the amount
of reusing the 'experience' should be increased.",
- }
Genetic Programming entries for
Roongroj Nopsuwanchai
Prabhas Chongstitvatana
Citations