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Markov Decision Processes with Their Applications (Hardcover)
Loot Price: R3,151
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Markov Decision Processes with Their Applications (Hardcover)
Series: Advances in Mechanics and Mathematics, 14
Expected to ship within 10 - 15 working days
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Markov decision processes (MDPs), also called stochastic dynamic
programming, were first studied in the 1960s. MDPs can be used to
model and solve dynamic decision-making problems that are
multiperiod and in stochastic circumstances. There are three basic
branches in MDPs: discrete-time MDPs, continuous-time MDPs and
semi-Markov decision processes. Starting from these three branches,
many generalized MDPs models have been applied to various practical
problems. These models include partially observable MDPs, adaptive
MDPs, MDPs in stochastic environments, and MDPs with multiple
objectives, constraints or imprecise parameters. MDPs have been
applied in many areas, such as communications, signal processing,
artificial intelligence, stochastic scheduling and manufacturing
systems, discrete event systems, management and economies. This
book examines MDPs and their applications in the optimal control of
discrete event systems (DESs), optimal replacement, and optimal
allocations in sequential online auctions.The book presents three
main topics: a new methodology for MDPs with discounted total
reward criterion; transformation of continuous-time MDPs and
semi-Markov decision processes into a discrete-time MDPs model,
thereby simplifying the application of MDPs; application of MDPs in
stochastic environments, which greatly extends the area where MDPs
can be applied. Each topic is used to study optimal control
problems or other types of problems.
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