Autonomous Robot Failure Recognition Design using Multi-Objective Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Zhang:2006:MLC,
  author =       "Yang Zhang",
  title =        "Autonomous Robot Failure Recognition Design using
                 Multi-Objective Genetic Programming",
  booktitle =    "2006 International Conference on Machine Learning and
                 Cybernetics",
  year =         "2006",
  pages =        "4563--4568",
  month =        aug,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-4244-0061-9",
  DOI =          "doi:10.1109/ICMLC.2006.258378",
  abstract =     "An evolutionary autonomous failure recognition
                 approach is presented using multi-objective genetic
                 programming in this paper. It is compared with the
                 conventional robot failure classification algorithm.
                 Detailed analysis of the evolved feature extractors is
                 tempted on investigated problems. We conclude MOGP is
                 an effective and practical way to automate the process
                 of failure recognition system design with better
                 recognition accuracy and more flexibility via
                 optimising feature extraction stage.",
  notes =        "Electronic and Electrical Engineering Department, The
                 University of Sheffield, S1 3JD, UK",
}

Genetic Programming entries for Yang Zhang

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