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• W2002581886 abstract "In this monograph we provided a tutorial on a family of sequential learning and decision problems known as the multi-armed bandit problems. We introduced a wide range of application scenarios for this learning framework, as well as its many different variants. The more detailed discussion has focused more on the stochastic bandit problems, with rewards driven by either an IID or a Markovian process, and when the environment consists of a single or multiple simultaneous users. We also presented literature on learning of MDPs, which captures coupling among the evolution of different options that a classical MAB problem does not." @default.
• W2002581886 created "2016-06-24" @default.
• W2002581886 creator A5053015746 @default.
• W2002581886 creator A5083047932 @default.
• W2002581886 date "2013-01-01" @default.
• W2002581886 modified "2023-09-25" @default.
• W2002581886 title "Online Learning Methods for Networking" @default.
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• W2002581886 doi "https://doi.org/10.1561/9781601989178" @default.
• W2002581886 hasPublicationYear "2013" @default.
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