Q-learning training enforces a relationship in which the current reward plus the next state's Q-value equals the Q-value from the original state.

“The way you train this is effectively by just enforcing exactly this. So you say the current reward plus the next state's uh Q function should be equal to the uh the Q function starting from the original state. So you effectively say R plus”