Hyun-Chang Yang

Papers

Total Citations

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About

Hyun-Chang Yang’s research centers on swarm robotics, machine learning, and evolutionary algorithms, with a particular focus on enabling autonomous robots to adapt to dynamic environments through behavior learning and evolution. His major contributions include pioneering the use of Support Vector Machines (SVM) for reinforcement learning in swarm robot systems, combined with distributed genetic algorithms that allow individual robots to exchange chromosomes via communication, facilitating cooperative adaptation. This work, detailed in his most-cited paper (2007, 6 citations), demonstrates how robots can independently assess their states and surroundings while collaborating to complete tasks—a critical advancement for scalable, flexible robotic swarms. Yang’s approach leverages structural risk minimization to enhance learning efficiency, distinguishing his methods from traditional neural-network-based techniques. Although his citation counts are modest, his research lays foundational groundwork for integrating SVM-based learning with evolutionary strategies in multi-robot systems, offering a robust framework for real-world applications like search-and-rescue or environmental monitoring. His dual-language publications (English and Korean) also highlight his commitment to disseminating findings across global and local research communities, making his work accessible to both international scholars and domestic robotics engineers.