対話的パラメータ最適化のための集団探索打ち切り型探索アルゴリズムの提案  [in Japanese] A Search Algorithm with Cancelleation of Population-based Search for Interactive Parameter Optimization  [in Japanese]

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Author(s)

    • 渡辺 晃生 Watanabe Akio
    • 東京大学大学院工学系研究科電気系工学専攻 Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo
    • 伊庭 斉志 Iba Hitoshi
    • 東京大学大学院情報理工学系研究科電子情報学専攻 Department of Information and Communication Engineering, Graduate School of Information Science and Technology, The University of Tokyo

Abstract

Interactive Evolutionary Computation (IEC) is a method to optimize parameters with subjective evaluation by human user, and it is applicable with the creative tasks like composition or coloration, which computer system was not able to deal with before. In IEC process, evolutionary computation, which is one of the multi-point search algorithms, is used to find an optimal parameter set which user likes. Evolutionary computation is designed for the environment in which the system can use long term of computational time. However in situations of interactive parameter optimization, since input from human user is needed, foundation of a good solution in very short computational time is required considering fatigue of users. In these situations, evolutionary computation which tries to find global optima with long computational time is not necessarily suitable. In this research, to find a good solution in interactive situations, we propose a new search algorithm with two stages of multi-point search and one-point search. From the results of mathematical benchmark tests, we found that our method is effective in the environment with limited number of evaluations, which contains large segment of conventional IEC applications. Additionally, we also show the effectiveness of our method with a real world application.

Interactive Evolutionary Computation (IEC) is a method to optimize parameters with subjective evaluation by human user, and it is applicable with the creative tasks like composition or coloration, which computer system was not able to deal with before. In IEC process, evolutionary computation, which is one of the multi-point search algorithms, is used to find an optimal parameter set which user likes. Evolutionary computation is designed for the environment in which the system can use long term of computational time. However in situations of interactive parameter optimization, since input from human user is needed, foundation of a good solution in very short computational time is required considering fatigue of users. In these situations, evolutionary computation which tries to find global optima with long computational time is not necessarily suitable. In this research, to find a good solution in interactive situations, we propose a new search algorithm with two stages of multi-point search and one-point search. From the results of mathematical benchmark tests, we found that our method is effective in the environment with limited number of evaluations, which contains large segment of conventional IEC applications. Additionally, we also show the effectiveness of our method with a real world application.

Journal

  • Transaction of the Japanese Society for Evolutionary Computation

    Transaction of the Japanese Society for Evolutionary Computation 3(2), 47-62, 2012

    The Japanese Society for Evolutionary Computation

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