3.8 Proceedings Paper

Fuzzy Ontology-based Intelligent Agent for High-School Student Learning in AI-FML Metaverse

Publisher

IEEE
DOI: 10.1109/FUZZ-IEEE55066.2022.9882549

Keywords

Fuzzy Ontology; Fuzzy Markup Language; High-School Student Learning; Intelligent Agent; AI-FML Metaverse

Funding

  1. Ministry of Science and Technology of Taiwan [MOST 110-2622-E-024-003-CC1, MOST 110-2221-E-024-009]

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This article discusses the importance of applying fuzzy ontology concepts and the Heart Sutra to artificial intelligence in English and fuzzy markup language learning for students. By using an intelligent agent on the AI-FML Metaverse platform, students can experience computational intelligence applications and combine fuzzy ontology, AI-FML, and the principles of the Heart Sutra. After evaluating its implementation, the intelligent agent proves to be effective in teaching, and students' interest and performance show an increasing tendency.
This article applies the fuzzy ontology concepts of Heart Sutra to artificial intelligence (AI) for elementary and high-school students learning English and fuzzy markup language (FML) in AI-FML Metaverse. Computational Intelligence (CI) is an imperative branch of AI and it includes fuzzy logic (FL), neural network (NN), and evolutionary computation (EC). Based on the technologies of reinforcement learning (RL), intelligent agent, ontology, and AI-FML human and machine co-learning, we propose a fuzzy ontology-based intelligent agent for young students to learn and experience CI applications, including basic concepts of FL, NN, and EC, on the AI-FML Metaverse platform. Additionally, we combine the core technologies of fuzzy ontology and AI-FML with the tenets of the Heart Sutra for constructing the intelligent agent in the AI-FML Metaverse with computational, perceptive, and cognitive intelligence. Moreover, we also apply the human semantic understanding of the Heart Sutra to explain the concept of the AI-FML Metaverse platform to elementary and high-school students to learn and experience CI. The intelligent agent interacts with the environment of the learning field and AI-FML Metaverse, it can help teachers and students evaluate learners' interest in each episode's learning content. Finally, it predicts their learning temperature in thermometers to present learners' performance in the learning contents, such as English or CI application. After evaluating the implementation of AI-FML Metaverse in the elementary school (grades 5-6), junior high school (grades 7-8), and senior high school (grades 10-12) students in Taiwan, we observe that the intelligent agent can work effectively and students' learning thermometer has an increasing tendency at the end of the 2021 fall semesters in AI-FML Metaverse and 2022 AI-FML winter camp in Taiwan.

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