Adversarial bandit problems: the power of randomization

author: Gabor Lugosi, Department of Economics and Business, Pompeu Fabra University
published: Nov. 16, 2010,   recorded: September 2010,   views: 383
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Description

In this tutorial we discuss sequential prediction problems in which the forecaster has limited information about the past outcomes of the sequence. We concentrate on the so-called "adversarial" framework in which no probabilistic is available for the sequence. We describe various models of limited feedback and pay special attention to the so-called "multi-armed bandit" problem. We discuss various randomized prediction methods and analyze their behavior.

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