Towards generalization by identification-based XCS in multi-steps problem. - Masaya Nakata; Fumiaki Sato; Keiki Takadama (NaBIC, 2011)

Enhancing Learning Capabilities by XCS with Best Action Mapping. - Masaya Nakata; Pier Luca Lanzi; Keiki Takadama (PPSN (1), 2012)

XCS with Adaptive Action Mapping. - Masaya Nakata; Pier Luca Lanzi; Keiki Takadama (SEAL, 2012)

Simple compact genetic algorithm for XCS. - Masaya Nakata; Pier Luca Lanzi; Keiki Takadama (IEEE Congress on Evolutionary Computation, 2013)

Selection strategy for XCS with adaptive action mapping. - Masaya Nakata; Pier Luca Lanzi; Keiki Takadama (GECCO, 2013)

Sleep Stage Estimation Using Synthesized Data of Heart Rate and Body Movement. - Yusuke Tajima; Masaya Nakata; Tomohiro Harada; Keiji Sato; Keiki Takadama (AAAI Spring Symposia, 2014)

A modified XCS classifier system for sequence labeling. - Masaya Nakata; Tim Kovacs; Keiki Takadama (GECCO, 2014)

Complete action map or best action map in accuracy-based reinforcement learning classifier systems. - Masaya Nakata; Pier Luca Lanzi; Tim Kovacs; Keiki Takadama (GECCO, 2014)

Personalized real-time sleep stage remote monitoring system. - Yusuke Tajima; Masaya Nakata; Keiki Takadama (ISMICT, 2014)

Archives-holding XCS Classifier System: A preliminary study. - Takahiro Komine; Masaya Nakata; Keiki Takadama (NaBIC, 2014)

Reusable knowledge by linkage-classifier in Accuracy-based Learning Classifier System. - Kotaro Usui; Masaya Nakata; Keiki Takadama (NaBIC, 2014)

Messy Coding in the XCS Classifier System for Sequence Labeling. - Masaya Nakata; Tim Kovacs; Keiki Takadama (PPSN, 2014)

How should Learning Classifier Systems cover a state-action space? - Masaya Nakata; Pier Luca Lanzi; Tim Kovacs; Will Neil Browne; Keiki Takadama (CEC, 2015)

Detecting shoplifting from customer behavior data by extended XCS-SL: Towards feature extraction on class-imbalanced sequence data. - Minato Sato; Kotaro Usui; Masaya Nakata; Keiki Takadama (CEC, 2015)

Extracting both generalized and specialized knowledge by XCS using Attribute Tracking and Feedback. - Keiki Takadama; Masaya Nakata (CEC, 2015)

XCS-SL: a rule-based genetic learning system for sequence labeling. - Masaya Nakata; Tim Kovacs; Keiki Takadama (Evol. Intell., 2015)

Rule reduction by selection strategy in XCS with adaptive action map. - Masaya Nakata; Pier Luca Lanzi; Keiki Takadama (Evol. Intell., 2015)

Evolutionary Algorithm for Uncertain Evaluation Function. - Yusuke Tajima; Masaya Nakata; Hiroyasu Matsushima; Yoshihiro Ichikawa; Hiroyuki Sato; Kiyohiko Hattori; Keiki Takadama (New Math. Nat. Comput., 2015)

XCS-DH: Minimal default hierarchies in XCS. - Tim Kovacs; Simon Rawles; Larry Bull; Masaya Nakata; Keiki Takadama (CEC, 2016)

Learning classifier system with deep autoencoder. - Kazuma Matsumoto; Yusuke Tajima; Rei Saito; Masaya Nakata; Hiroyuki Sato; Tim Kovacs; Keiki Takadama (CEC, 2016)

A modified cuckoo search algorithm for dynamic optimization problems. - Yuta Umenai; Fumito Uwano; Yusuke Tajima; Masaya Nakata; Hiroyuki Sato; Keiki Takadama (CEC, 2016)

International Workshop on Evolutionary Rule-Based Machine Learning Workshop (IWERML) Welcome & Organization. - Karthik Kuber; Masaya Nakata; Kamran Shafi (GECCO (Companion), 2016)

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)

Preventing Incorrect Opinion Sharing with Weighted Relationship Among Agents. - Rei Saito; Masaya Nakata; Hiroyuki Sato; Tim Kovacs; Keiki Takadama (HCI (5), 2016)

Proceedings in Adaptation, Learning and Optimization. - Masaya Nakata; Kazuhisa Chiba (IES, 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)

Reinforcement Learning with Internal Reward for Multi-Agent Cooperation: A Theoretical Approach. - Fumito Uwano; Naoki Tatebe; Masaya Nakata; Keiki Takadama; Tim Kovacs (EAI Endorsed Trans. Collab. Comput., 2016)

Optimization of Aircraft Landing Route and Order: An approach of Hierarchical Evolutionary Computation. - Akinori Murata; Masaya Nakata; Hiroyuki Sato; Tim Kovacs; Keiki Takadama (EAI Endorsed Trans. Self Adapt. Syst., 2016)

Theoretical XCS parameter settings of learning accurate classifiers. - Masaya Nakata; Will N. Browne; Tomoki Hamagami; Keiki Takadama (GECCO, 2017)

From Extraction to Generation of Design Information -Paradigm Shift in Data Mining via Evolutionary Learning Classifier System. - Kazuhisa Chiba; Masaya Nakata (ICCS, 2017)

Effect of parameter sharing for multimodal deep autoencoders. - Hayato Sasaki; Masaya Nakata; Fumiya Hamatsu; Tomoki Hamagami (SMC, 2017)

An Analysis of Rule Deletion Scheme in XCS on Reinforcement Learning Problem. - Masaya Nakata; Tomoki Hamagami (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)

Theoretical adaptation of multiple rule-generation in XCS. - Masaya Nakata; Will N. Browne; Tomoki Hamagami (GECCO, 2018)

Investigation about Control of False Positive Rate for Automatic Sperm Detection in Assisted Reproductive Technology. - Hayato Sasaki; Masaya Nakata; Mizuki Yamamoto; Teppei Takeshima; Yasushi Yumura; Tomoki Hamagami (SMC, 2018)

Complex-Valued-based Learning Classifier System for POMDP Environments. - Keiki Takadama; Daichi Yamazaki; Masaya Nakata; Hiroyuki Sato (CEC, 2019)

How XCS can prevent misdistinguishing rule accuracy: a preliminary study. - Masaya Nakata; Will Neil Browne (GECCO (Companion), 2019)

Competitive-Adaptive Algorithm-Tuning of Metaheuristics inspired by the Equilibrium Theory: A Case Study. - Kei Nishihara 001; Masaya Nakata (CEC, 2020)

MOEA/D-S3: MOEA/D using SVM-based Surrogates adjusted to Subproblems for Many objective optimization. - Takumi Sonoda; Masaya Nakata (CEC, 2020)

Self-adaptation of XCS learning parameters based on learning theory. - Motoki Horiuchi; Masaya Nakata (GECCO, 2020)

An overview of LCS research from IWLCS 2019 to 2020. - David Pätzel; Anthony Stein; Masaya Nakata (GECCO Companion, 2020)

Learning classifier systems: from principles to modern systems. - Anthony Stein; Masaya Nakata (GECCO Companion, 2020)

Comparison of Adaptive Differential Evolution Algorithms on the MOEA/D-DE Framework. - Kei Nishihara 001; Masaya Nakata (CEC, 2021)

Convergence analysis of rule-generality on the XCS classifier system. - Yoshiki Nakamura 003; Motoki Horiuchi; Masaya Nakata (GECCO, 2021)

Extended Learning Optimality Theory for the XCS classifier system on Multiple Reward Scheme. - Motoki Horiuchi; Masaya Nakata (SSCI, 2021)

Learning Optimality Theory for Accuracy-Based Learning Classifier Systems. - Masaya Nakata; Will N. Browne (IEEE Trans. Evol. Comput., 2021)

Surrogate-assisted Differential Evolution with Adaptation of Training Data Selection Criterion. - Kei Nishihara 001; Masaya Nakata (SSCI, 2022)

Automatic Construction of Loading Algorithms With Interactive Genetic Programming. - Yusuke Hiruta; Kei Nishihara 001; Yuji Koguma; Masakazu Fujii; Masaya Nakata (IEEE Access, 2022)

Theoretical Analysis of Accuracy-Based Fitness on Learning Classifier Systems. - Rui Sugawara; Masaya Nakata (IEEE Access, 2022)

Multiple Classifiers-Assisted Evolutionary Algorithm Based on Decomposition for High-Dimensional Multiobjective Problems. - Takumi Sonoda; Masaya Nakata (IEEE Trans. Evol. Comput., 2022)

Utilizing the Expected Gradient in Surrogate-assisted Evolutionary Algorithms. - Kei Nishihara 001; Masaya Nakata (GECCO Companion, 2023)

High-Dimensional Expensive Optimization by Classification-based Multiobjective Evolutionary Algorithm with Dimensionality Reduction. - Yuma Horaguchi; Masaya Nakata (SICE, 2023)

A Dual Surrogate-Based Evolutionary Algorithm for High-Dimensional Expensive Multiobjective Optimization Problems. - Yuma Horaguchi; Masaya Nakata (CEC, 2024)

A Random Forest-Assisted Local Search for Expensive Permutation-based Combinatorial Optimization Problems. - Takashi Ikeguchi; Shun Sudo; Yuji Koguma; Masaya Nakata (CEC, 2024)

Oversampling-Guided Search for Evolutionary Multiobjective Optimization. - Norihiro Kimoto; Yuma Horaguchi; Masaya Nakata (CEC, 2024)

A Surrogate-Assisted Partial Optimization for Expensive Constrained Optimization Problems. - Kei Nishihara 001; Masaya Nakata (PPSN (2), 2024)

A Variable-Length Fuzzy Set Representation for Learning Fuzzy-Classifier Systems. - Hiroki Shiraishi; Rongguang Ye; Hisao Ishibuchi; Masaya Nakata (PPSN (3), 2024)

Evolutionary multiobjective optimization assisted by scalarization function approximation for high-dimensional expensive problems. - Yuma Horaguchi; Kei Nishihara 001; Masaya Nakata (Swarm Evol. Comput., 2024)

High-Dimensional Expensive Multiobjective Optimization Using a Surrogate-Assisted Multifactorial Evolutionary Algorithm. - Yuma Horaguchi; Masaya Nakata (GECCO, 2025)

A surrogate-assisted memetic algorithm for permutation-based combinatorial optimization problems. - Takashi Ikeguchi; Kei Nishihara 001; Yo Kawauchi; Yuji Koguma; Masaya Nakata (Swarm Evol. Comput., 2025)

X-KAN: Optimizing Local Kolmogorov-Arnold Networks via Evolutionary Rule-Based Machine Learning. - Hiroki Shiraishi; Hisao Ishibuchi; Masaya Nakata (CoRR, 2025)

A Class Inference Scheme With Dempster-Shafer Theory for Learning Fuzzy-Classifier Systems. - Hiroki Shiraishi; Hisao Ishibuchi; Masaya Nakata (CoRR, 2025)

Adapting Rule Representation With Four-Parameter Beta Distribution for Learning Classifier Systems. - Hiroki Shiraishi; Yohei Hayamizu; Tomonori Hashiyama; Keiki Takadama; Hisao Ishibuchi; Masaya Nakata (CoRR, 2025)