If I understand, an action is a set of joints, then the robot does a trial and receives a reward depending on the distance from the target.
In that case, you are not doing sequential learning. For example, in Cartpole, you have to learn the sequence of actions ‘left left left right right left’. A new action depends on the previous state and action.
Here, when you know the target, you can directly compute a set of angles, wherever was the arm’s initial position. (or maybe the target is moving, so the new state depends on the last position of the target)
After, this does not explain why it fails, as actor critics are solving non-sequential tasks. But it is quite sub-optimal.