Search Results for author: Naoyuki Kubota

Found 8 papers, 2 papers with code

Privacy-preserving Continual Federated Clustering via Adaptive Resonance Theory

1 code implementation7 Sep 2023 Naoki Masuyama, Yusuke Nojima, Yuichiro Toda, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota

In the clustering domain, various algorithms with a federated learning framework (i. e., federated clustering) have been actively studied and showed high clustering performance while preserving data privacy.

Clustering Continual Learning +2

A Study on AI-FML Robotic Agent for Student Learning Behavior Ontology Construction

no code implementations18 Jun 2020 Chang-Shing Lee, Mei-Hui Wang, Wen-Kai Kuan, Zong-Han Ciou, Yi-Lin Tsai, Wei-Shan Chang, Lian-Chao Li, Naoyuki Kubota, Tzong-Xiang Huang, Eri Sato-Shimokawara, Toru Yamaguchi

In this paper, we propose an AI-FML robotic agent for student learning behavior ontology construction which can be applied in English speaking and listening domain.

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

no code implementations22 Jan 2019 Chang-Shing Lee, Mei-Hui Wang, Li-Chuang Chen, Yusuke Nojima, Tzong-Xiang Huang, Jinseok Woo, Naoyuki Kubota, Eri Sato-Shimokawara, Toru Yamaguchi

This paper applies a genetic algorithm and fuzzy markup language to construct a human and smart machine cooperative learning system on game of Go.

Game of Go

PFML-based Semantic BCI Agent for Game of Go Learning and Prediction

no code implementations10 Jan 2019 Chang-Shing Lee, Mei-Hui Wang, Li-Wei Ko, Bo-Yu Tsai, Yi-Lin Tsai, Sheng-Chi Yang, Lu-An Lin, Yi-Hsiu Lee, Hirofumi Ohashi, Naoyuki Kubota, Nan Shuo

This paper presents a semantic brain computer interface (BCI) agent with particle swarm optimization (PSO) based on a Fuzzy Markup Language (FML) for Go learning and prediction applications.

Brain Computer Interface Game of Go

Human and Smart Machine Co-Learning with Brain Computer Interface

no code implementations19 Feb 2018 Chang-Shing Lee, Mei-Hui Wang, Li-Wei Ko, Naoyuki Kubota, Lu-An Lin, Shinya Kitaoka, Yu-Te Wang, Shun-Feng Su

Machine learning has become a very popular approach for cybernetics systems, and it has always been considered important research in the Computational Intelligence area.

Brain Computer Interface

FML-based Dynamic Assessment Agent for Human-Machine Cooperative System on Game of Go

1 code implementation16 Jul 2017 Chang-Shing Lee, Mei-Hui Wang, Sheng-Chi Yang, Pi-Hsia Hung, Su-Wei Lin, Nan Shuo, Naoyuki Kubota, Chun-Hsun Chou, Ping-Chiang Chou, Chia-Hsiu Kao

In this paper, we demonstrate the application of Fuzzy Markup Language (FML) to construct an FML-based Dynamic Assessment Agent (FDAA), and we present an FML-based Human-Machine Cooperative System (FHMCS) for the game of Go.

Decision Making Game of Go

FML-based Prediction Agent and Its Application to Game of Go

no code implementations16 Apr 2017 Chang-Shing Lee, Mei-Hui Wang, Chia-Hsiu Kao, Sheng-Chi Yang, Yusuke Nojima, Ryosuke Saga, Nan Shuo, Naoyuki Kubota

In this paper, we present a robotic prediction agent including a darkforest Go engine, a fuzzy markup language (FML) assessment engine, an FML-based decision support engine, and a robot engine for game of Go application.

Game of Go

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