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For questions related to the multi-armed bandit (MAB) problem, in which a fixed limited set of resources must be allocated between competing (alternative) choices in a way that maximizes their expected gain, when each choice's properties are only partially known at the time of allocation.
5
votes
Accepted
What is the probability of selecting the greedy action in a 0.5-greedy selection method for ...
I read section 2.2 of Sutton and Barto, and I understand your confusion: the $\epsilon$-greedy algorithm is not defined precisely on page 27-28. Selecting an action randomly "every once in awhile" wit …
2
votes
Why do we use $X_{I_t,t}$ and $v_{I_t}$ to denote the reward received and the at time step $...
Isn't the distribution independent of the time the arm $i$ was chosen?
Each one of the two references you describe assumes the context of the random bandit problem proposed by Robbins (1952) where t …
4
votes
Accepted
How do I recognise a bandit problem?
The bandit problem has one state, in which you are allowed to choose one lever among $n$ levers to pull.
Why is there just one state in the formulation of this bandit problem?
There is one state …