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Reference Vector Adaptation and Mating Selection Strategy via Adaptive Resonance Theory-based Clustering for Many-objective Optimization



Takato Kinoshita , Naoki Masuyama , Yiping Liu , Yusuke Nojima , Hisao Ishibuchi

* This paper is currently under review 

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Class-wise Classifier Design Capable of Continual Learning using Adaptive Resonance Theory-based Topological Clustering



Naoki Masuyama , Itsuki Tsubota , Yusuke Nojima , Hisao Ishibuchi

* This paper is currently under review. arXiv admin note: substantial text overlap with arXiv:2201.10713 

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Adaptive Resonance Theory-based Topological Clustering with a Divisive Hierarchical Structure Capable of Continual Learning



Naoki Masuyama , Narito Amako , Yuna Yamada , Yusuke Nojima , Hisao Ishibuchi

* This paper is currently under review 

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Effects of Different Optimization Formulations in Evolutionary Reinforcement Learning on Diverse Behavior Generation



Victor Villin , Naoki Masuyama , Yusuke Nojima

* This paper has been accepted for the presentation in IEEE SSCI 2021 

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Multi-label Classification via Adaptive Resonance Theory-based Clustering



Naoki Masuyama , Yusuke Nojima , Chu Kiong Loo , Hisao Ishibuchi


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Identifying Properties of Real-World Optimisation Problems through a Questionnaire



Koen van der Blom , Timo M. Deist , Vanessa Volz , Mariapia Marchi , Yusuke Nojima , Boris Naujoks , Akira Oyama , Tea Tušar

* Book Chapter (Under review) 

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Towards Realistic Optimization Benchmarks: A Questionnaire on the Properties of Real-World Problems



Koen van der Blom , Timo M. Deist , Tea Tušar , Mariapia Marchi , Yusuke Nojima , Akira Oyama , Vanessa Volz , Boris Naujoks

* 2 pages, GECCO2020 Poster Paper 

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A GFML-based Robot Agent for Human and Machine Cooperative Learning on Game of Go



Chang-Shing Lee , Mei-Hui Wang , Li-Chuang Chen , Yusuke Nojima , Tzong-Xiang Huang , Jinseok Woo , Naoyuki Kubota , Eri Sato-Shimokawara , Toru Yamaguchi


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