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Results tagged with comparison
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user 36821
For questions that involve the comparison of two AI concepts, terms or expressions. An example of such a question is: how does machine learning compare to deep learning?
3
votes
Why are policy iteration and value iteration studied as separate algorithms?
Policy iteration is made up of two steps. The first is a full policy evaluation, where a value function is calculated for the current policy. The second is policy improvement, where the policy is made …
- 5,030
6
votes
How can a probability density value be used for the likelihood calculation?
The probability density is used to 'measure how good' the parameters are because it is a natural way of quantifying if these parameters are good for the observed data.
Also, as the notation often caus …
- 5,030
1
vote
Accepted
Are the state-action values and the state value function equivalent for a given policy?
In general they are not the same and that should be clear as to why -- mathematically you are conditioning on an extra random variable being known in the state-action value function. You have the corr …
- 5,030
2
votes
Accepted
What are the differences between SARSA and Q-learning?
The main difference between the two is that Q-learning is an off policy algorithm. That is, we learn about an policy that is different to the one we choose to make actions. To see this, lets look at t …
- 5,030
3
votes
Accepted
What is the difference between A2C and Q-Learning, and when to use one over the other?
The major difference between A2C and Q-Learning are what the algorithms learn. In A2C, and policy gradient algorithms in general, the policy is directly parameterised, i.e. we have $\pi_\theta (a|s)$. …
- 5,030
2
votes
1
answer
261
views
Are these two definitions of the state-action value function equivalent?
I have been reading the Sutton and Barto textbook and going through David Silvers UCL lecture videos on YouTube and have a question on the equivalence of two forms of the state-action value function w …
- 5,030
3
votes
Accepted
What is the difference between terminal state, nonterminal states and normal states?
Terminal state is always the same in the sense that it represents the same thing, that the episode is over. They don’t need to be the exact same state; for instance you could have an $n$ by $n$ grid w …
- 5,030
8
votes
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 $t$ …
- 5,030
11
votes
Accepted
What exactly is the advantage of double DQN over DQN?
In $Q$-learning there is what is known as a maximisation bias. That is because the update target is $r + \gamma \max_a Q(s,a)$. If you slightly overestimate your $Q$-value then this error gets compoun …
- 5,030
9
votes
Accepted
What is the difference between Q-learning, Deep Q-learning and Deep Q-network?
In Q-learning (and in general value based reinforcement learning) we are typically interested in learning a Q-function, $Q(s, a)$. This is defined as
$$Q(s, a) = \mathbb{E}_\pi\left[ G_t | S_t = s, A_ …
- 5,030