# Tag Info

### Are Q-learning and SARSA the same when action selection is greedy?

If we write the pseudo-code for the SARSA algorithm we first initialise our hyper-parameters etc. and then initialise $S_t$, which we use to choose $A_t$ from our policy $\pi(a|s)$. Then for each $t$ ...
• 4,197
Accepted

### Is Q-learning only capable of learning a deterministic policy?

If we assume a tabular setting, then Q-learning converges to the optimal state-action value function, from which an optimal policy can be derived, provided a few conditions are met. In finite MDPs, ...
• 35k
Accepted

### Can Q-learning be used in a POMDP?

The usual (as presented in Reinforcement Learning: An Introduction) $Q$-learning and SARSA algorithms use (and update) a function of a state $s$ and action $a$, $Q(s, a)$. These algorithms assume that ...
• 35k
Accepted

### When do SARSA and Q-Learning converge to optimal Q values?

The true answers are 1 and 3. 1 is true because the required conditions for tabular Q-learning to converge is that each state action pair will be visited infinitely often, and Q-learning learns ...
• 4,197