Action Space

The action space is the complete set of outputs a robot policy can produce at each timestep. For a robot arm it typically includes joint positions, joint velocities, or end-effector poses (Cartesian position + quaternion); for a mobile robot it includes wheel velocities or steering commands. Action spaces are described as either discrete (a finite menu of actions) or continuous (real-valued vectors). The dimensionality and representation of the action space strongly influences how easy it is to train a stable policy: end-effector delta-pose spaces are often easier for imitation learning, while joint-torque spaces give finer force control but require more careful normalization.