Yasuhiro Tanaka
Papers
1
Total Citations
7
H-Index
1
About
Yasuhiro Tanaka is a pioneering researcher in the field of robotics and artificial intelligence, with a particular focus on reinforcement learning and its application to real-world robotic systems. His most-cited work, "Reinforcement Learning for a Real Robot in a Real Environment" (1996), has garnered 7 citations and stands as a foundational contribution to bridging the gap between theoretical machine learning algorithms and practical, embodied robotics. This paper demonstrated how reinforcement learning could be effectively implemented on physical robots operating in unstructured, dynamic environments—a significant challenge at the time. Tanaka’s research addresses critical issues in autonomous decision-making, sensorimotor control, and adaptive behavior, laying the groundwork for modern approaches to robot learning. His work is notable for its emphasis on real-world validation, moving beyond simulations to tackle the complexities of noisy sensors, mechanical limitations, and unpredictable surroundings. By integrating reinforcement learning with physical robotics, Tanaka has influenced subsequent developments in autonomous navigation, manipulation, and human-robot interaction. His contributions remain relevant for students and researchers exploring how intelligent agents can learn from interaction with their environment, making him a key figure in the evolution of practical AI.
Research Focus
Key Achievements
Top Papers
- 1Reinforcement Learning for a Real Robot in a Real Environment.7 citations · 1996