Pivot-based Generalization towards an Adapting Changing Environment

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  • SATO Keiji
    Graduate School of Informatics and Engineering, The University of Electro-Communications
  • SATO Hiroyuki
    Graduate School of Informatics and Engineering, The University of Electro-Communications
  • TAKADAMA Keiki
    Graduate School of Informatics and Engineering, The University of Electro-Communications

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  • 環境変化に適応するためのピボット型一般化
  • カンキョウ ヘンカ ニ テキオウ スル タメ ノ ピボットガタ イッパンカ

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Abstract

This paper proposes a concept and mechanism of the pivot-based generalization which can adapt to changing environment by introducing s# which represents two opposite situations while # which represents one situation in the context of Learning Classifier Systems. Intensive experiments, have revealed that (1) the pivot-based generalization can generalize individuals in the 2-objective Knapsack problem and real world water bus route optimization problem; (2) the sharp distance which represents distance between each individuals of the generalize individual contributes to controlling the number of s# individuals; (3) the pivot-based generalization of individuals can clarify the feature of solution space.

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