PSO-based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application

no code implementations • 24 Feb 2018 • Chang-Shing Lee, Mei-Hui Wang, Chi-Shiang Wang, Olivier Teytaud, Jialin Liu, Su-Wei Lin, Pi-Hsia Hung

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, and the proposed agent is according to the response data from a conventional test and an item response theory.

Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

no code implementations • 26 Jan 2018 • Chang-Shing Lee, Mei-Hui Wang, Tzong-Xiang Huang, Li-Chung Chen, Yung-Ching Huang, Sheng-Chi Yang, Chien-Hsun Tseng, Pi-Hsia Hung, Naoyuki Kubota

Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class.

BIG-bench Machine Learning

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

1 code implementation • 16 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