A sensor tagging approach for reusing building blocks of knowledge in learning classifier systems

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

@InProceedings{Chen:2015:CECa,
  author =       "Liang-Yu Chen and Po-Ming Lee and Tzu-Chien Hsiao",
  booktitle =    "IEEE Congress on Evolutionary Computation (CEC 2015)",
  title =        "A sensor tagging approach for reusing building blocks
                 of knowledge in learning classifier systems",
  year =         "2015",
  pages =        "2953--2960",
  abstract =     "During the last decade, the extraction and reuse of
                 building blocks of knowledge for the learning process
                 of Extended Classifier System (XCS) in Multiplexer
                 (MUX) problem domain have been demonstrate feasible by
                 using Code Fragment (CF) (i.e. a tree-based structure
                 ordinarily used in the field of Genetic Programming
                 (GP)) as the representation of classifier conditions
                 (the resulting system was called XCSCFC). However, the
                 use of the tree-based structure may lead to the
                 bloating problem and increase in time complexity when
                 the tree grows deep. Therefore, we proposed a novel
                 representation of classifier conditions for the XCS,
                 named Sensory Tag (ST). The XCS with the ST as the
                 input representation is called XCSSTC. The experiments
                 of the proposed method were conducted in the MUX
                 problem domain. The results indicate that the XCSSTC is
                 capable of reusing building blocks of knowledge in the
                 MUX problems. The current study also discussed about
                 two different aspects of reusing of building blocks of
                 knowledge. Specifically, we proposed the attribution
                 selection' part and the 'logical relation between the
                 attributes' part.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CEC.2015.7257256",
  ISSN =         "1089-778X",
  month =        may,
  notes =        "Also known as \cite{7257256}",
}

Genetic Programming entries for Liang-Yu Chen Po-Ming Lee Tzu-Chien Hsiao

Citations