Using non-determinism to improve robustness of robot programs generated by genetic programming

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

@InProceedings{oai:CiteSeerPSU:421290,

• author = "Thanut Sukkarnjanonth and Prabhas Chongstitvatana",
• title = "Using non-determinism to improve robustness of robot programs generated by genetic programming",
• booktitle = "Proc. of 4th National Computer Science and Engineering Conference (NCSEC 2000)",
• year = "2000",
• pages = "81--85",
• address = "Queen Sirikit National Convention Center, Bangkok, Thailand",
• month = "16-17 " # nov,
• keywords = "genetic algorithms, genetic programming, Robustness, Robot programs, Non-determinism, Evolutionary Computation",
• citeseer-isreferencedby = "oai:CiteSeerPSU:59076; oai:CiteSeerPSU:72057",
• citeseer-references = "\cite{oai:CiteSeerPSU:511796}",
• annote = "The Pennsylvania State University CiteSeer Archives",
• language = "en",
• oai = "oai:CiteSeerPSU:421290",
• rights = "unrestricted",
• URL = "http://citeseer.ist.psu.edu/421290.html",
• abstract = "Robustness is essential for programs generated by Genetic Programming (GP). This paper presents a method to improve the robustness. The method employs non-determinism in two ways: one is to evolve robot programs in noisy environments and another is to use probabilistic branch in the function set. The experiment is carried out on robot navigation problems. The result of the experiment shows that the robustness of robot programs has been improved. The analysis shows that the robustness is caused by the acquired experience and the amount of reuse of this experience while performing the task.",
• notes = "http://216.239.59.104/search?q=cache:2CkcwU8FR1UJ:cp.eng.chula.ac.th/publication.html+Sukkarnjanonth&hl=en",

}

Genetic Programming entries for Thanut Sukkarnjanonth Prabhas Chongstitvatana

Citations