Unveiling the Potential and Limitations of Visual Reinforcement Learning: An Experimental Analysis on the Cart-Pole Inverted Pendulum System
Sanghyun Ryoo, Soohee Han · 2023
Reinforcement learning can handle what traditional control theory can not cope with. In the field of visual reinforcement learning given only a partially observed high-dimensional image state, the agent still can learn a policy to achieve certain tasks. In this paper, we show the potential and limitations of visual reinforcement learning with an experiment on cart-pole balancing tasks both in simulation and semi-real environment systems.