A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences
author: Odalric-Ambrym Maillard,
INRIA Lille - Nord Europe
published: Aug. 2, 2011, recorded: July 2011, views: 3357
published: Aug. 2, 2011, recorded: July 2011, views: 3357
Slides
Related content
Report a problem or upload files
If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Description
We consider a Kullback-Leibler-based algorithm for the stochastic multi-armed bandit problem in the case of distributions with finite supports (not necessarily known beforehand), whose asymptotic regret matches the lower bound of Burnetas and Katehakis (1996). Our contribution is to provide a finite-time analysis of this algorithm; we get bounds whose main terms are smaller than the ones of previously known algorithms with finite-time analyses (like UCB-type algorithms).
Link this page
Would you like to put a link to this lecture on your homepage?Go ahead! Copy the HTML snippet !
Write your own review or comment: