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Generalized Risk-Aversion in Stochastic Multi-Armed Bandits

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arxiv 1405.0833 v1 pith:6EPZJRJK submitted 2014-05-05 cs.LG stat.ML

Alexander Zimin , Rasmus Ibsen-Jensen , Krishnendu Chatterjee This is my paper
classification cs.LGstat.ML
keywords meanmulti-armedregretstochasticachievealgorithmbanditbandits
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We consider the problem of minimizing the regret in stochastic multi-armed bandit, when the measure of goodness of an arm is not the mean return, but some general function of the mean and the variance.We characterize the conditions under which learning is possible and present examples for which no natural algorithm can achieve sublinear regret.

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