부산대학교 도서관

In this paper, we propose a brain–computer interface(BCI)-based Human-in-the-Loop(Hit-Loop) agent for human and artificial intelligence(AI) colearning in music listening and appreciation with an Artificial Intelligence of Things(AIoT) application. The novel BCI-based Hit-Loop agentcontains human intelligencewith BCI-based AIoT-Fuzzy Markup Language(FML) and BCI-FML agents, as well as machine intelligencewith AI-FML Hit-Loopand AIoT-FML agents. We used FML to facilitate communication between humans and the AI-FML robotsthrough an AIoT-FML Learning Tool(AIoT-FML-LT), which was the core technology of the AI-FML Hit-Loop agentfor the BCI-based music listening and appreciation application. Furthermore, the novel AIoT-FML-LTin conjunction with the BCI-FMLand AIoT-FML agentswas developed and presented for music listening and student learning. Moreover, the BCI-based AIoT-FMLand AI-FML Hit-Loop agentswere applied in English language learning, and the AIoT-FML-LTassisted in measuring student learning performance in Taiwan and Japan. The human-like high-level knowledge base and rule base were constructed by various domain experts, as well as the personalized electroencephalography (EEG) and student English learning data sets collected using the BCI device and AIoT-FML-LT, respectively, and were applied to machine learning models such as deep learning and particle swarm optimization. Additionally, the AIoT-FML-LTwas connected to the AIoT-FML Hit-Loop agentfor human and robot colearning. The relationship between human perceptions and the AIoT-FML Hit-Loop agentin terms of eyes, ears, nose, tongue, body, and braincorresponding to sights, sounds, smells, tastes, objects of touch, and mindare discussed. Finally, the students learned human language and AI language by using the AI-FML robotsand AIoT-FML-LTtogether with the human English learning and AI-FML machine learning models, respectively. The experimental results reveal that the BCI-based Hit-Loop agentfor human and AI-FML robotcolearning in conjunction with AIoT applications can effectively facilitate music listening and appreciation application as well as English listening in Taiwan and Japan. The learning behavior and performance of the students also improved after incorporation of the human and robot colearning model.