Obtaining System Robustness by Mimicking Natural Mechanisms

Created by W.Langdon from gp-bibliography.bib Revision:1.4534

  author =       "Song Zhan and Julian F. Miller and Andy M. Tyrrell",
  title =        "Obtaining System Robustness by Mimicking Natural
  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