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In this paper, the Robotic Assistant Agent for student and machineco-learning on AI-FML practice with AIoT application is presented. Thestructure of AI-FML contains three parts, including fuzzy logic, neuralnetwork, and evolutionary computation. Besides, the Robotic Assistant Agent(RAA) can assist students and machines in co-learning English and AI-FMLpractice based on the robot Kebbi Air and AIoT-FML learning tool. Since Sept.2019, we have introduced an Intelligent Speaking English Assistant (ISEA) Appand AI-FML platform to English and computer science learning classes at twoelementary schools in Taiwan. We use the collected English-learning data totrain a predictive regression model based on students' monthly examinationscores. In Jan. 2021, we further combined the developed AI-FML platform with anovel AIoT-FML learning tool to enhance students' interests in learning Englishand AI-FML with basic hands-on practice. The proposed RAA is responsible forreasoning students' learning performance and showing the results on theAIoT-FML learning tool after communicating with the AI-FML platform. Theexperimental results and the collection of students' feedback show that thiskind of learning model is popular with elementary-school and high-schoolstudents, and the learning performance of elementary-school students isimproved.

Robotic Assistant Agent for Student and Machine Co-Learning on AI-FML Practice with AIoT Application