Abstract
In this chapter, we add an extra layer of complexity to our models of decision making by introducing the idea of a state-dependent decision process. The processes we will consider can either be deterministic or stochastic. To begin with, we will assume that the process must terminate by an a priori fixed time T (a “finite horizon” model). In principle, decisions can be made at times t = 0, 1, 2,..., T — 1, although the actual number of decisions made may be fewer than T if the process terminates early as a consequence of the actions taken. Models that have no a priori restriction on the number of decisions to be taken (“infinite horizon” models) will be considered in the next chapter.
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© 2007 Springer-Verlag London Limited
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(2007). Markov Decision Processes. In: Game Theory. Springer Undergraduate Mathematics Series. Springer, London. https://doi.org/10.1007/978-1-84628-636-0_3
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DOI: https://doi.org/10.1007/978-1-84628-636-0_3
Publisher Name: Springer, London
Print ISBN: 978-1-84628-423-6
Online ISBN: 978-1-84628-636-0
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