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20162021
most citedPSO-based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application

50 citations · 119 across the 12 of their papers we have counts for

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10 papers · 1 filter

cs.AI2021

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,…

cs.AI2020★ 1 cited

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…

cs.AI2019

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…

cs.AI2019★ 4 cited

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…

cs.AI2018★ 50 cited

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…

cs.AI2018★ 4 cited

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…

cs.AI2018★ 6 cited

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…

cs.AI2017★ 10 cited

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…

cs.AI2017★ 2 cited

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…

cs.AI2016★ 40 cited

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)…