[D] State or Action based rewards for RL

Is it better to have the reward function be better when the agent makes a good move, or if it’s in a good state. Eg: the reward for an agent in a good state that makes a net negative move is higher than that of an agent in a bad state that makes a net negative move or vice versa.

The most basic example I can think is if you have an env with a “target” input of 1 or …

machinelearning rl