I'm working on a paper that uses ε-greedy algorithms for choosing episodes of a sarsa q-learning algorithms. I searched for algorithm but couldn't get so much. Can you please give me the algorithms and a little explanations about it?

• This question asks to list a potentially large body of work. Community votes, please: is this too broad? – Raphael Feb 25 '16 at 17:24
• @Raphael what you mean? what is the problem? – virtouso Feb 25 '16 at 18:19
• @mtk99 "Working on", not "working with". It would be unusual to share a link to a paper that's not complete yet. – David Richerby Feb 25 '16 at 20:16
• @DavidRicherby On the other hand, it is also unusual to ask strangers on the internet to explain the topic of the paper you are writing to you. – Raphael Feb 25 '16 at 21:00
• Can you share a link to the paper? – Juan Leni Feb 25 '16 at 21:52

ε-greedy is just a way to promote exploration in Reinforcement Learning. I would not classify SARSA or Q-Learning as ε-greedy algorithms.

The latter are very common reinforcement learning algorithms and you can definitely can find lots of material about them.

I would suggest to have a look at this classic book (the draft for the second edition is available for free)

https://webdocs.cs.ualberta.ca/~sutton/book/the-book.html

Another shorter and excellent resource is (have a look at chapter 21):

Russell SJ, Norvig P, Davis E. Artificial intelligence: a modern approach. Upper Saddle River, NJ: Prentice Hall; 2010.

EDIT:

The paper you posted is using SARSA(λ), it is not the same as SARSA. You will need to go through a few Sutton chapters for that to make sense. You won't find it in Russell.

The link to SARSA(λ) in Sutton (1998) HTML version is here: webdocs.cs.ualberta.ca/~sutton/book/ebook/node77.html

However, I think you will need to read at least chapter 6 before jumping into eligibility traces

• i think the paper meant sarsa from ε-greedy algorithm but im looking for a trace algorithm that how it really works – virtouso Feb 25 '16 at 16:10
• This is the link to SARSA($\lambda$) in Sutton (1998) HTML version: webdocs.cs.ualberta.ca/~sutton/book/ebook/node77.html , however I think you will need to read at least chapter 6 before jumping into eligibility traces – Juan Leni Feb 25 '16 at 16:16
• can you give just a simple trace example or explanation? the book just shows the algorithm. i cant understand it well. – virtouso Feb 25 '16 at 20:04