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Learning in a Changing World: Restless Multiarmed Bandit With Unknown Dynamics

IEEE Transactions on Information Theory, no. 3 (2013): 1902-1916

Cited: 61|Views28
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Abstract

We consider the restless multiarmed bandit problem with unknown dynamics in which a player chooses one out of $N$ arms to play at each time. The reward state of each arm transits according to an unknown Markovian rule when it is played and evolves according to an arbitrary unknown random process when it is passive. The performance of an a...More

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Qing Zhao
Qing Zhao
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