Takato Tatsumi

 

Research field

Learning classifier system: evolutionary computation and reinforcement learning

Papers

Journal

  • Takato Tatusmi, Takahiro Komine, Masaya Nakata, Hiroyuki Sato, and Keiki Takadama:

    “A Learning Classifier System that Adapts Accuracy Criterion”,
    Transaction of the Japanese Society for Evolutionary Computation Vol. 6 (2015) No. 2 p. 90-103Download »

  • ・Kazuma Matsumoto, Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, and Keiki Takadama:

    “XCSR Learning from Compressed Data Acquired by Deep Neural Network”,
    Journal of Advanced Computational Intelligence and Intelligent Informatics Vol.21 No.5 p. 856-867Download »

    ・Caili Zhang, Takato Tatsumi, Masaya Nakata, and Keiki Takadama:

    “Approach to Clustering with Variance-Based XCS”,
    Journal of Advanced Computational Intelligence and Intelligent Informatics Vol.21 No.5 p. 885-894Download »

    ・Takato Tatsumi, Hiroyuki Sato, and Keiki Takadama:

    “Learning Classifier System Based on Mean of Reward”,
    Journal of Advanced Computational Intelligence and Intelligent Informatics Vol.21 No.5 p. 895-906Download »

    ・Takato Okudo, Tomohiro Yamaguchi, Akinori Murata, Takato Tatsumi, Fumito Uwano, and Keiki Takadama:

    “Supporting the Exploration of the Learning Goals for a Continuous Learner Toward Creative Learning”,
    Journal of Advanced Computational Intelligence and Intelligent Informatics Vol.21 No.5 p. 907-916Download »

    Conference

  • Takato Tatsumi, Takahiro Komine, Hiroyuki Sato, Keiki Takadama:

    “Handling Different Level of Unstable Reward Environment Through an Estimation of Reward Distribution in XCS”,
    IEEE Congress on Evolutionary Computation (CEC) 2015 pp. 2973-2980, May 25-28, 2015, Sendai, Japan.Download »

  • Takato Tatsumi, Takahiro Komine, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:

    “Variance-based Learning Classifier System without Convergence of Reward Estimation”,
    Genetic and Evolutioary Computation Conference (GECCO) pp. 67-68, July 2016, Denver, USA.Download »

  • Caili Zhang, Takato Tatsumi, Masaya Nakata, Keiki Takadama, Hiroyuki Sato, Tim Kovacs:

    “Extracting Different Abstracted Level Rule with Variance-Based LCS”,
    2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS) pp. 160-165, August 2016, Hokkaido, Japan.Download »

  • Haruyuki Ishii, Keiki Takadama, Akinori Murata, Fumito Uwano, Takato Tatsumi, Yuta Umenai, Kazuma Matsumoto, Hiroyuki Kamata, Takayuki Ishida, Seisuke Fukuda, Shujiro Sakai, Shinichiro Sawai:

    “The Robust Spacecraft Location Estimation Algorithm Toward The Misdetection Crater and The Undetected Crater in SLIM”,
    The 31th International Symposium on Space Technology and Science (ISTS2017), July 2017, Ehime, Japan.

  • Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:

    “Applying Variance-based Learning Classifier System without Convergence of Reward Estimation into Various Reward Distribution”,
    IEEE Congress on Evolutionary Computation (CEC) pp. 2630-2637, June 2017, Donostia, Spain.Download »

  • Takato Tatsumi, Hiroyuki Sato, Keiki Takadama:

    “Automatic Adjustment of Selection Pressure based on Range of Reward in Learning Classifier System”,
    Genetic and Evolutioary Computation Conference (GECCO) pp. 505-512, July 2017, Berlin, Germany.Download »

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