Q-Learning

1984년 도입 · 논문 1,734편에서 사용

Q-Learning is an off-policy temporal difference control algorithm: $$Q\left(S\_{t}, A\_{t}\right) \leftarrow Q\left(S\_{t}, A\_{t}\right) + \alpha\left[R_{t+1} + \gamma\max\_{a}Q\left(S\_{t+1}, a\right) - Q\left(S\_{t}, A\_{t}\right)\right] $$ The learned action-value function $Q$ directly approximates $q\_{*}$, the optimal action-value function, independent of the policy being followed. Source: Sutton and Barto, Reinforcement Learning, 2nd Edition