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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Markov Decision Processes
Erschienen in: Game Theory
Verlag: Springer London
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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.