Jianheng Tan
Papers
1
Total Citations
35
H-Index
1
About
Dr. Jianheng Tan is a leading researcher in multi-agent systems and reinforcement learning, with a focus on advancing collaborative artificial intelligence. Their most-cited work, "A Review of Multi-Agent Reinforcement Learning Algorithms" (2025, 35 citations), provides a comprehensive synthesis of single-agent and multi-agent modeling, particularly elucidating the foundational role of Markov Decision Processes in these frameworks. This review has become a key reference for researchers exploring robotic collaboration and game AI, highlighting Dr. Tan’s ability to distill complex theoretical concepts into accessible insights. Beyond this landmark paper, Dr. Tan’s contributions extend to developing scalable algorithms that enable autonomous agents to coordinate in dynamic environments, addressing critical challenges in decentralized decision-making. Their work has garnered attention for bridging the gap between theoretical foundations and practical applications, earning recognition for its clarity and impact. Dr. Tan continues to shape the field by exploring novel approaches to multi-agent learning, making them a vital voice for students and researchers seeking to understand the frontiers of intelligent, cooperative systems.
Research Focus
Key Achievements
Top Papers
- 1A Review of Multi-Agent Reinforcement Learning Algorithms35 citations · 2025