Multi-Armed Bandit Processes

Xiaoqiang Cai, Xianyi Wu and Xian Zhou
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Xiaoqiang Cai: The Chinese University of Hong Kong
Xianyi Wu: East China Normal University
Xian Zhou: Macquarie University

Chapter Chapter 6 in Optimal Stochastic Scheduling, 2014, pp 225-252 from Springer

Abstract: Abstract This chapter studies the powerful tool for stochastic scheduling, using theoretically elegant multi-armed bandit processes to maximize expected total discounted rewards. Multi-armed bandit models form a particular type of optimal resource allocation problems, in which a number of machines or processors are to be allocated to serve a set of competing projects (arms). We introduce the classical theory for multi-armed bandit processes in Section 6.1, and consider open bandit processes in which infinitely many arms are allowed in Section 6.2. An extension to generalized open bandit processes is given in Section 6.3. Finally, a concise account for closed bandit processes in continuous time is presented in Section 6.4.

Keywords: Optimal Policy; Reward Rate; Index Policy; Bandit Problem; Decision Epoch (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-1-4899-7405-1_6

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