50 citations · 119 across the 12 of their papers we have counts for
12 papers
AI-Fuzzy Markup Language with Computational Intelligence for High-School Student Learning
Chang-Shing Lee, Mei-Hui Wang, Yusuke Nojima +2
Computational Intelligence (CI), which includes fuzzy logic (FL), neural network (NN), and evolutionary computation (EC), is an imperative branch of artificial intelligence (AI). A…
Robotic Assistant Agent for Student and Machine Co-Learning on AI-FML Practice with AIoT Application
Chang-Shing Lee, Mei-Hui Wang, Zong-Han Ciou +6
In this paper, the Robotic Assistant Agent for student and machine co-learning on AI-FML practice with AIoT application is presented. The structure of AI-FML contains three parts,…
A Study on AI-FML Robotic Agent for Student Learning Behavior Ontology Construction
Chang-Shing Lee, Mei-Hui Wang, Wen-Kai Kuan +8
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. The AI-FML robo…
A GFML-based Robot Agent for Human and Machine Cooperative Learning on Game of Go
Chang-Shing Lee, Mei-Hui Wang, Li-Chuang Chen +6
This paper applies a genetic algorithm and fuzzy markup language to construct a human and smart machine cooperative learning system on game of Go. The genetic fuzzy markup language…
PFML-based Semantic BCI Agent for Game of Go Learning and Prediction
Chang-Shing Lee, Mei-Hui Wang, Li-Wei Ko +8
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 app…
PSO-based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application
Chang-Shing Lee, Mei-Hui Wang, Chi-Shiang Wang +4
This paper proposes an agent with particle swarm optimization (PSO) based on a Fuzzy Markup Language (FML) for students learning performance evaluation and educational applications…
Human and Smart Machine Co-Learning with Brain Computer Interface
Chang-Shing Lee, Mei-Hui Wang, Li-Wei Ko +5
Machine learning has become a very popular approach for cybernetics systems, and it has always been considered important research in the Computational Intelligence area. Neverthele…
Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning
Chang-Shing Lee, Mei-Hui Wang, Tzong-Xiang Huang +6
An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The…
Ontology-based Adaptive e-Textbook Platform for Student and Machine Co-Learning
Noel Nuo Wi Tay, Sheng-Chi Yang, Chang-Shing Lee +1
The use of electronic textbooks (e-book) has been heavily studied over the years due to their flexibility, accessibility, interactivity and extensibility. Yet current shortcomings…
FML-based Dynamic Assessment Agent for Human-Machine Cooperative System on Game of Go
Chang-Shing Lee, Mei-Hui Wang, Sheng-Chi Yang +7
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 Co…
FML-based Prediction Agent and Its Application to Game of Go
Chang-Shing Lee, Mei-Hui Wang, Chia-Hsiu Kao +5
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…
Human vs. Computer Go: Review and Prospect
Chang-Shing Lee, Mei-Hui Wang, Shi-Jim Yen +6
The Google DeepMind challenge match in March 2016 was a historic achievement for computer Go development. This article discusses the development of computational intelligence (CI)…