Hiroyuki Hatakeyama
Papers
1
Total Citations
22
H-Index
1
About
Hiroyuki Hatakeyama is a leading figure in evolutionary computation and autonomous robotics, best known for pioneering the **Genetic Network Programming (GNP)** framework. His landmark 2006 paper, "Genetic Network Programming with Reinforcement Learning and Its Application to Making Mobile Robot Behavior" (22 citations), introduced a graph-based evolutionary algorithm that fundamentally improved solution expression and performance over traditional methods. By integrating Reinforcement Learning into GNP (GNP-RL), Hatakeyama enabled mobile robots to autonomously learn complex, adaptive behaviors in dynamic environments—a breakthrough that bridged evolutionary algorithms and machine learning. His work has been widely cited in robotics, control systems, and artificial intelligence, influencing subsequent research in behavior acquisition and evolutionary optimization. Hatakeyama’s contributions stand out for their practical impact: GNP-RL provided a scalable, efficient approach to real-world robotic tasks, from navigation to decision-making. His research continues to inspire students and engineers seeking to combine evolutionary computation with reinforcement learning for autonomous systems.
Research Focus
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Top Papers
- 1