Handling different level of unstable reward environment through an estimation of reward distribution in XCS. - Takato Tatsumi; Takahiro Komine; Hiroyuki Sato; Keiki Takadama (CEC, 2015)

Variance-based Learning Classifier System without Convergence of Reward Estimation. - Takato Tatsumi; Takahiro Komine; Masaya Nakata; Hiroyuki Sato; Tim Kovacs; Keiki Takadama (GECCO (Companion), 2016)

Extracting Different Abstracted Level Rule with Variance-Based LCS. - Caili Zhang; Takato Tatsumi; Masaya Nakata; Keiki Takadama; Hiroyuki Sato; Tim Kovacs (SCIS&ISIS, 2016)

Applying variance-based Learning Classifier System without Convergence of Reward Estimation into various Reward distribution. - Takato Tatsumi; Hiroyuki Sato; Tim Kovacs; Keiki Takadama (CEC, 2017)

Automatic adjustment of selection pressure based on range of reward in learning classifier system. - Takato Tatsumi; Hiroyuki Sato; Keiki Takadama (GECCO, 2017)

XCSR Learning from Compressed Data Acquired by Deep Neural Network. - Kazuma Matsumoto; Takato Tatsumi; Hiroyuki Sato; Tim Kovacs; Keiki Takadama (J. Adv. Comput. Intell. Intell. Informatics, 2017)

Supporting the Exploration of the Learning Goals for a Continuous Learner Toward Creative Learning. - Takato Okudo; Tomohiro Yamaguchi 002; Akinori Murata; Takato Tatsumi; Fumito Uwano; Keiki Takadama (J. Adv. Comput. Intell. Intell. Informatics, 2017)

Learning Classifier System Based on Mean of Reward. - Takato Tatsumi; Hiroyuki Sato; Keiki Takadama (J. Adv. Comput. Intell. Intell. Informatics, 2017)

Approach to Clustering with Variance-Based XCS. - Caili Zhang; Takato Tatsumi; Masaya Nakata; Keiki Takadama (J. Adv. Comput. Intell. Intell. Informatics, 2017)

Study of Analytical Methods on the Relationship between Sleep Quality and Stress with a focus on Human Circadian Rhythm. - Ryo Takano; Satoshi Hasegawa; Yuta Umenai; Takato Tatsumi; Keiki Takadama; Toru Shimuta; Toru Yabe; Hideo Matsumoto (AAAI Spring Symposia, 2018)

XCSR based on compressed input by deep neural network for high dimensional data. - Kazuma Matsumoto; Ryo Takano; Takato Tatsumi; Hiroyuki Sato; Tim Kovacs; Keiki Takadama (GECCO (Companion), 2018)

XCS-CR: determining accuracy of classifier by its collective reward in action set toward environment with action noise. - Takato Tatsumi; Tim Kovacs; Keiki Takadama (GECCO (Companion), 2018)

Classifier generalization for comprehensive classifiers subsumption in XCS. - Caili Zhang; Takato Tatsumi; Hiyoyuki Sato; Tim Kovacs; Keiki Takadama (GECCO (Companion), 2018)

XCS for Missing Attributes in Data. - Takato Tatsumi; Keiki Takadama (SCIS&ISIS, 2018)

Knowledge Extraction from XCSR Based on Dimensionality Reduction and Deep Generative Models. - Masakazu Tadokoro; Satoshi Hasegawa; Takato Tatsumi; Hiroyuki Sato; Keiki Takadama (CEC, 2019)

Comparison of Statistical Table- and Non-Statistical Table-based XCS in Noisy Environments. - Takato Tatsumi; Keiki Takadama (CEC, 2019)

XCS-CR for handling input, output, and reward noise. - Takato Tatsumi; Keiki Takadama (GECCO (Companion), 2019)

Local Covering: Adaptive Rule Generation Method Using Existing Rules for XCS. - Masakazu Tadokoro; Satoshi Hasegawa; Takato Tatsumi; Hiroyuki Sato; Keiki Takadama (CEC, 2020)