Are Q-learning and SARSA with greedy selection equivalent?

Question

The difference between Q-learning and SARSA is that Q-learning compares the current state and the best possible next state, whereas SARSA compares the current state against the

Answer 1

If an optimal policy has already formed, SARSA with pure greedy and Q-learning are same.

However, in training, we only have a policy or sub-optimal policy, SARSA with pure greedy will only converge to the "best" sub-optimal policy available without trying to explore the optimal one, while Q-learning will do, because of , which means it tries all actions available and choose the max one.