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1999 | Buch

Further Topics on Discrete-Time Markov Control Processes

verfasst von: Onésimo Hernández-Lerma, Jean Bernard Lasserre

Verlag: Springer New York

Buchreihe : Stochastic Modelling and Applied Probability

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This book presents the second part of a two-volume series devoted to a sys­ tematic exposition of some recent developments in the theory of discrete­ time Markov control processes (MCPs). As in the first part, hereafter re­ ferred to as "Volume I" (see Hernandez-Lerma and Lasserre [1]), interest is mainly confined to MCPs with Borel state and control spaces, and possibly unbounded costs. However, an important feature of the present volume is that it is essentially self-contained and can be read independently of Volume I. The reason for this independence is that even though both volumes deal with similar classes of MCPs, the assumptions on the control models are usually different. For instance, Volume I deals only with nonnegative cost­ per-stage functions, whereas in the present volume we allow cost functions to take positive or negative values, as needed in some applications. Thus, many results in Volume Ion, say, discounted or average cost problems are not applicable to the models considered here. On the other hand, we now consider control models that typically re­ quire more restrictive classes of control-constraint sets and/or transition laws. This loss of generality is, of course, deliberate because it allows us to obtain more "precise" results. For example, in a very general context, in §4.

Inhaltsverzeichnis

Frontmatter
7. Ergodicity and Poisson’s Equation
Abstract
This chapter deals with noncontrolled Markov chains and presents important background material used in later chapters. The reader may omit it and refer to it as needed.
Onésimo Hernández-Lerma, Jean Bernard Lasserre
8. Discounted Dynamic Programming with Weighted Norms
Abstract
In this chapter we consider the infinite-horizon discounted cost problem for a Markov control model \( (X,A,\{ A(x)\left| x \right. \in X\} ,Q,c). \) We already studied this problem using dynamic programming and linear programming in Chapters 4 and 6, respectively. Here we use again dynamic programming, so it is important to state at the outset the differences between this chapter and Chapter 4.
Onésimo Hernández-Lerma, Jean Bernard Lasserre
9. The Expected Total Cost Criterion
Abstract
Let \( M = (X,A,\{ A(x)\left| x \right. \in X\} ,Q,c) \) be the Markov control model (MCM) in §8.2. In this chapter we study the expected total cost (ETC) criterion defined as
$$ {V_1}(\pi ,x): = E_x^\pi \left[ {\sum\limits_{t = 0}^\infty {c({x_t} - {a_t})} } \right] for \pi \in \Pi ,x \in X, $$
(9.1.1)
so the corresponding (optimal) value function is
$$ V_1^*(x): = \mathop {\inf }\limits_\Pi {V_1}(\pi ,x), x \in X. $$
(9.1.2)
Onésimo Hernández-Lerma, Jean Bernard Lasserre
10. Undiscounted Cost Criteria
Abstract
Infinite-horizon Markov control problems can be roughly classified as being “discounted” or “undiscounted”. The former, which have been the main subject of Chapter 4 and Chapter 8, are basically well understood in the sense that their theory can be safely considered to be complete. This is not the case for undiscounted problems—in fact, to start with, “undiscounted” can have several different meanings.
Onésimo Hernández-Lerma, Jean Bernard Lasserre
11. Sample Path Average Cost
Abstract
In this chapter we study AC-related criteria, some of which have already been studied in previous chapters from a different viewpoint. We begin by introducing some notation and definitions, and then we outline the contents of this chapter.
Onésimo Hernández-Lerma, Jean Bernard Lasserre
12. The Linear Programming Approach
Abstract
In this chapter we study the linear programming (LP) approach to Markov control problems. Our ultimate goal is to show how a Markov control problem can be approximated by finite linear programs.
Onésimo Hernández-Lerma, Jean Bernard Lasserre
Backmatter
Metadaten
Titel
Further Topics on Discrete-Time Markov Control Processes
verfasst von
Onésimo Hernández-Lerma
Jean Bernard Lasserre
Copyright-Jahr
1999
Verlag
Springer New York
Electronic ISBN
978-1-4612-0561-6
Print ISBN
978-1-4612-6818-5
DOI
https://doi.org/10.1007/978-1-4612-0561-6