Obtaining System Robustness by Mimicking Natural Mechanisms

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Zhan:2009:cec,

• author = "Song Zhan and Julian F. Miller and Andy M. Tyrrell",
• title = "Obtaining System Robustness by Mimicking Natural Mechanisms",
• booktitle = "2009 IEEE Congress on Evolutionary Computation",
• year = "2009",
• editor = "Andy Tyrrell",
• pages = "3032--3039",
• address = "Trondheim, Norway",
• month = "18-21 " # may,
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• isbn13 = "978-1-4244-2959-2",
• file = "P118.pdf",
• DOI = "doi:10.1109/CEC.2009.4983326",
• abstract = "Real working agents normally operate in dynamic changing environments. These changes could either affect the efficiency of the agents' performance or even damage the functionality of the agent. Robustness is the key requirement to solve this problem. Inspired by nature, this paper demonstrates two mechanisms that contribute to individual's robustness in changing environments: evolution and degeneracy. Through evolution in damaging environment, evolved agents have to cope with changes in the environment and acquire robustness. Through degeneracy, individuals can maintain their fitness even when some damaged parts are involved in system function.",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming",
• notes = "CEC 2009 - A joint meeting of the IEEE, the EPS and the IET. IEEE Catalog Number: CFP09ICE-CDR",

}

Genetic Programming entries for Song Zhan Julian F Miller Andrew M Tyrrell

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