Q-learning

Unlike the SARSA algorithm, Q-learning uses the current knowledge of the action-value function (Q-function) to update the target policy greedily:

$Q(S_t,A_t)=Q(S_t,A_t)+\alpha (R_t+\gamma \underset{a}{max}Q(S_{t+1},a)-Q(S_t,A_t))$