2019
A Comparison of Action Spaces for Learning Manipulation Tasks
IROS 2019poster
Designing reinforcement learning (RL) problems that can produce delicate and precise manipulation policies requires careful choice of the reward function, state, and action spaces. Much prior work on applying RL to manipulation tasks has defined the action space in terms of direct joint torques or r…