2018
Reinforcement Learning of Depth Stabilization with a Micro Diving Agent
ICRA 2018poster
Reinforcement learning (RL) allows robots to solve control tasks through interaction with their environment. In this paper we study a model-based value-function RL approach, which is suitable for computationally limited robots and light embedded systems. We develop a diving agent, which uses the RL…