Combinatorial Network Optimization With Unknown Variables: Multi-Armed Bandits With Linear Rewards and Individual Observations

We formulate the following combinatorial multi-armed bandit (MAB) problem: There are N random variables with unknown mean that are each instantiated in an i.i.d. fashion over time. At each time multiple random variables can be selected, subject to an arbitrary constraint on weights associated with t...

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Bibliographic Details
Published in:	IEEE/ACM transactions on networking Vol. 20; no. 5; pp. 1466 - 1478
Main Authors:	Yi Gai, Krishnamachari, B., Jain, R.
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.10.2012 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithm design and analysis Algorithms Combinatorial analysis Combinatorial network optimization Computation Formulations Indexes Mathematical analysis Mathematical models multi-armed bandits (MABs) Networks online learning Optimization Policies Polynomials Radiation detectors Random variables Studies Upper bound
ISSN:	1063-6692, 1558-2566
Online Access:	Get full text
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