Shang‐Pin Ma
Papers
1
Total Citations
6
H-Index
1
About
Shang-Pin Ma is a researcher whose work lies at the intersection of artificial intelligence, robotics, and machine learning, with a particular focus on multi-agent systems and strategic decision-making. His most notable contribution is the development of a hybrid learning approach for RoboCup, a premier international robotics competition, where he applied a combination of reinforcement learning and case-based reasoning to enhance team strategies in dynamic, adversarial environments. This work, published in 2013 and garnering 6 citations, demonstrates his ability to integrate theoretical AI methods with practical, real-world robotic challenges. Ma’s research addresses the critical problem of adaptive strategy formation in autonomous agents, offering insights that extend beyond robotics into areas like autonomous vehicles and game AI. While his citation count reflects a focused, emerging impact, his contributions to RoboCup highlight his hands-on approach to advancing AI in competitive, time-sensitive settings. For students and researchers, Ma’s work serves as a model for bridging algorithmic innovation with tangible, performance-driven outcomes in multi-agent systems.
Research Focus
Key Achievements
Top Papers
- 1Applying hybrid learning approach to RoboCup's strategy6 citations · 2013