Analysis Of Robustness Of Robot Programs Generated By Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{oai:CiteSeerPSU:511796,

• title = "Analysis Of Robustness Of Robot Programs Generated By Genetic Programming",
• author = "Roongroj Nopsuwanchai and Prabhas Chongstitvatana",
• booktitle = "First Asian Sympoium on Industrial Automation and Robotics BITEC",
• year = "1999",
• address = "Bangkok, Thailand",
• month = "6-7 " # may,
• keywords = "genetic algorithms, genetic programming",
• citeseer-isreferencedby = "oai:CiteSeerPSU:81384",
• annote = "The Pennsylvania State University CiteSeer Archives",
• language = "en",
• oai = "oai:CiteSeerPSU:511796",
• rights = "unrestricted",
• URL = "http://citeseer.ist.psu.edu/cache/papers/cs/20674/http:zSzzSzwww.cp.eng.chula.ac.thzSzfacultyzSzpjwzSzpaperzSznopsuwanchai.pdf/nopsuwanchai99analysis.pdf",
• URL = "http://citeseer.ist.psu.edu/511796.html",
• size = "5 pages",
• 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

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