학술논문

A Study on AI-FML Robotic Agent for Student Learning Behavior Ontology Construction
Document Type
Conference
Source
2020 International Symposium on Community-centric Systems (CcS) Community-centric Systems (CcS), 2020 International Symposium on. :1-6 Sep, 2020
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Robotics and Control Systems
Signal Processing and Analysis
Robots
Cognition
Artificial intelligence
Ontologies
Speech recognition
Education
Neural networks
AI-FML
Agent
Robot
Fuzzy Machine Learning
Ontology
Learning Behavior
Language
Abstract
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 robotic agent with the ontology contains the perception intelligence, computational intelligence, and cognition intelligence for analyzing student learning behavior. In addition, there are three intelligent agents, including a perception agent, a computational agent, and a cognition agent in the AI-FML robotic agent. We deploy the perception agent and the cognition agent on the robot Kebbi Air. Moreover, the computational agent with the Deep Neural Network (DNN) model is performed in the cloud and can communicate with the perception agent and cognition agent via the Internet. The proposed AI-FML robotic agent is applied in Taiwan and tested in Japan. The experimental results show that the agents can be utilized in the human and machine co-learning model for the future education.