Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Introduction to Neural Networks with Java
Introduction to Neural Networks with Java
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In this research, we focus on the state space construction problem in cases where the state space exhibits some hierarchical dependencies. In the case of the control of a robot's motion, it is believed there exist a strong correlation between the current position and the current speed. For positions close to the goal area, it is necessary to define an area for slowing down whereas a high speed motion is convenient for distant positions. We conduct several experiments to evaluate the effects of combining Self Organizing Map and grid-based representations to autonomously build such hierarchical structures. The results showed that with an extended acceleration range and a more detailed control, the hierarchically built state spaces permitted to achieve a smoother convergence, a better accuracy of learning and a more stable control.