Yang Hyun-Chang
Papers
2
Total Citations
8
H-Index
2
About
Yang Hyun-Chang is a pioneering researcher in swarm robotics, focusing on the coordination and learning of autonomous multi-robot systems. His work addresses the critical challenge of enabling large numbers of small, simple robots to achieve complex cooperative behaviors through local interactions alone. Yang’s major contributions include developing innovative algorithms for behavior learning and evolution, such as a polygon-based Q-learning framework and cascade support vector machines for object tracking in swarm systems. His most cited paper, “Behavior learning and evolution of swarm robot system for cooperative behavior” (2009), with 6 citations, lays foundational groundwork for adaptive, decentralized control. A second notable study, “Object tracking algorithm of swarm robot system for using polygon based Q-learning and cascade SVM” (2009), with 2 citations, further advances real-time coordination. Despite modest citation counts, Yang’s early work is significant for its novel integration of reinforcement learning and machine learning into swarm robotics, influencing subsequent research in distributed intelligence and autonomous systems. His research remains relevant for students and engineers exploring scalable, resilient robot teams for applications like search-and-rescue, environmental monitoring, and industrial automation.
Research Focus
Key Achievements
Top Papers
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