# Tag Info

Epsilon greedy is unaffected by scaling of rewards, it always selects a random action with a probability of epsilon. On the other hand, if we look at the formulation of UCB (Section 2.7 of Reinforcement Learning, Sutton and Barto): $$A_t \doteq \underset{a}{\operatorname{argmax}} [\mathcal{Q}_t(a) + c \sqrt{\frac{\ln t}{N_t(a)}}]$$ Where \$Q_t(a)= \frac{R_1 +...