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

Chang-Shing Lee, Mei‐Hui Wang, Wen-Kai Kuan, Zong-Han Ciou, Yi-Lin Tsai, Weishan Chang, Lian‐Chao Li, Naoyuki Kubota, Tzong-Xiang Huang, Eri Sato-Shimokawara, Toru Yamaguchi

发表年份
2020
引用次数
6

摘要

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.

关键词

OntologyComputer scienceArtificial intelligenceIntelligent agentPerceptionCognitionRobotCognitive roboticsDomain (mathematical analysis)Human–computer interaction

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