Wen-Kai Kuan

Papers

Total Citations

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About

Wen-Kai Kuan is a leading researcher at the intersection of artificial intelligence, fuzzy logic, and the Internet of Things (AIoT), with a focus on human-robot co-learning systems. His work centers on developing intelligent agents that bridge the gap between human behavior and machine cognition, particularly through the innovative application of Fuzzy Markup Language (FML) and genetic learning mechanisms. Kuan’s most impactful contribution is the creation of AI-FML robotic agents that enable real-world co-learning between humans and AI, as demonstrated in his highly cited 2021 paper on a BCI-based hit-loop agent for AIoT applications (11 citations). His 2020 study on AI-FML agents for the robotic game of Go (9 citations) showcases how fuzzy machine learning—integrating XGBoost and genetic algorithms—can drive adaptive decision-making in competitive environments. Additionally, his work on ontology construction for student learning behavior (6 citations) applies these principles to education, modeling perception, computational, and cognition intelligence. With a cumulative impact of over 26 citations across his top papers, Kuan is recognized for advancing practical AI systems that learn alongside humans, making him a notable figure in the evolution of intelligent, interactive robotics.