A Multitasks Learning Approach to Autonomous Agent based on Genetic Network Programming

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  title =        "A Multitasks Learning Approach to Autonomous Agent
                 based on Genetic Network Programming",
  author =       "Yang Yang and Shingo Mabu and Kotaro Hirasawa",
  pages =        "1937--1943",
  booktitle =    "Proceedings of the 2012 IEEE Congress on Evolutionary
  year =         "2012",
  editor =       "Xiaodong Li",
  month =        "10-15 " # jun,
  DOI =          "doi:10.1109/CEC.2012.6256457",
  address =      "Brisbane, Australia",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, Genetic
                 Network Programming, Evolutionary programming, Parallel
                 and distributed algorithms",
  abstract =     "The standard methodology in machine learning is to
                 learn one problem at a time. But, many real-world
                 problems are complex and have multitasks, and it is a
                 bit hard to learn them well by one machine learning
                 approach. So, the simultaneous learning of several
                 tasks has been considered, that is, so-called multitask
                 learning. This paper describes a new approach to the
                 autonomous agent problem using the multitask learning
                 scheme based on Genetic Network Programming (GNP),
                 called ML-GNP, where each GNP is used to learn one
                 corresponding task. MLGNP has some characteristics,
                 such as distribution, interaction and autonomy, which
                 are helpful for learning multitask problems. The
                 experimental results illustrate that ML-GNP can give
                 much better performance than learning all the tasks of
                 the problem by one GNP algorithm.",
  notes =        "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the
                 EPS and the IET.",

Genetic Programming entries for Yang Yang Shingo Mabu Kotaro Hirasawa