Evolutionary construction and adaptation of intelligent systems

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Jose M. Font and Daniel Manrique and Juan Rios",
  title =        "Evolutionary construction and adaptation of
                 intelligent systems",
  journal =      "Expert Systems with Applications",
  volume =       "37",
  number =       "12",
  pages =        "7711--7720",
  year =         "2010",
  ISSN =         "0957-4174",
  DOI =          "doi:10.1016/j.eswa.2010.04.070",
  URL =          "http://www.sciencedirect.com/science/article/B6V03-501FPHF-C/2/9a2d947791e5706c203b3fed536a0e36",
  keywords =     "genetic algorithms, genetic programming, Evolutionary
                 computation, Intelligent systems, Rule-based systems,
                 Fuzzy rule-based systems, Artificial neural networks,
                 Medical prognosis",
  abstract =     "This paper introduces evolutionary techniques for
                 automatically constructing intelligent self-adapting
                 systems, capable of modifying their inner structure in
                 order to learn from experience and self-adapt to a
                 changing environment. These evolutionary techniques
                 comprise an evolutionary system that is engineered by
                 grammar-guided genetic programming, enabling the
                 development of sub-symbolic and symbolic intelligent
                 systems: artificial neural networks and knowledge-based
                 systems, respectively. A context-free-grammar based
                 codification system for artificial neural networks and
                 rules, an initialisation method and a crossover
                 operator have been designed to properly balance the
                 exploration and exploitation capabilities of the
                 proposed system. This speeds up the convergence process
                 and avoids trapping in local optima. This system has
                 been applied to a medical domain: the detection of knee
                 injuries from the analysis of isokinetic time series.
                 The results of the evolved symbolic and sub-symbolic
                 intelligent systems have been statistically compared
                 with each other as part of a quantitative and
                 qualitative performance analysis.",

Genetic Programming entries for Jose M Font Daniel Manrique Gamo Juan Rios Carrion