WU Hong-yan
Papers
2
Total Citations
29
H-Index
2
About
Dr. Hong-yan Wu is a researcher in multi-robot systems, specializing in hierarchical reinforcement learning, swarm intelligence, and task allocation. Her most influential work, "A Pursuit-Evasion Algorithm Based on Hierarchical Reinforcement Learning" (2009, 27 citations), introduced a novel approach using the Option method to decompose complex pursuit-evasion tasks in dynamic 2D environments, demonstrating significant efficiency gains over traditional Q-learning. This contribution has been foundational for researchers working on multi-robot coordination and adversarial games. Dr. Wu also advanced the field of multi-robot task allocation with her paper "Multi-robot task allocation based on swarm intelligence" (2009), where she proposed a hybrid particle swarm optimization and ant colony optimization (PSOACO) mechanism for forming robot coalitions in both loosely and tightly-coupled tasks. Her work bridges reinforcement learning and bio-inspired algorithms, offering practical solutions for large-scale robotic systems. With her pioneering algorithms and clear comparative validations, Dr. Wu has made lasting contributions to autonomous robotics, inspiring further research in distributed intelligence and cooperative control.
Research Focus
Key Achievements
Top Papers
- 1A Pursuit-Evasion Algorithm Based on Hierarchical Reinforcement Learning27 citations · 2009
- 2Multi-robot task allocation based on swarm intelligence2 citations · 2009