A Learning Classifier System Based on Genetic Network Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4496

  author =       "Xianneng Li and Kotaro Hirasawa",
  title =        "A Learning Classifier System Based on Genetic Network
  booktitle =    "2013 IEEE International Conference on Systems, Man,
                 and Cybernetics (SMC 2013)",
  year =         "2013",
  pages =        "1323--1328",
  address =      "Manchester",
  month =        "13-16 " # oct,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, genetic
                 network programming, learning classifier systems,
                 niching, fitness sharing, reinforcement learning",
  DOI =          "doi:10.1109/SMC.2013.229",
  size =         "6 pages",
  abstract =     "Recent advances in Learning Classifier Systems (LCSs)
                 have shown their sequential decision-making ability
                 with a generalisation property. In this paper, a novel
                 LCS named extended rule-based Genetic Network
                 Programming (XrGNP) is proposed. Different from most of
                 the current LCSs, the rules are represented and
                 discovered through a graph-based evolutionary algorithm
                 GNP, which consequently has the distinct expression
                 ability to model and evolve the decision-making rules.
                 XrGNP is described in details in which its unique
                 features are explicitly mapped. Experiments on
                 benchmark and real-world multi-step problems
                 demonstrate the effectiveness of XrGNP.",
  notes =        "Also known as \cite{6721982}",

Genetic Programming entries for Xianneng Li Kotaro Hirasawa