If you were to map this to an RL setting, then an “action” consists of choosing a real-valued 4D vector. The model produces a distribution over these actions in the form of 4 independent 1D Normal distributions, from which a single action is sampled.
The “reward” is just the negative of the loss, which is the MSE between the target (y) and the sampled action (samples).