Titlebook: Discrete-Time Markov Control Processes; Basic Optimality Cri Onésimo Hernández-Lerma,Jean Bernard Lasserre Book 1996 Springer Science+Busin

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Infinite-Horizon Discounted-Cost Problems,inite-horizon problems, but for many purposes it is convenient to introduce the fiction that the optimization horizon is infinite. Certainly, for instance, processes of capital accumulation for an economy, or some problems on inventory or portfolio management, do not necessarily have a natural stopp

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The Linear Programming Formulation, principle applicable to almost any class of OCPs, deterministic or stochastic, in discrete or continuous time, constrained or unconstrained, with finite or infinite optimization horizon—some references are given in §6.6. The preferred techniques, on the other hand, include the Lagrange multipliers

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0172-4568 y of discrete-time Markov control processes (MCPs). Interest is mainly confined to MCPs with Borel state and control (or action) spaces, and possibly unbounded costs and noncompact control constraint sets. MCPs are a class of stochastic control problems, also known as Markov decision processes, cont

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https://doi.org/10.1007/978-981-15-3473-7ite or infinite optimization horizon—some references are given in §6.6. The preferred techniques, on the other hand, include the Lagrange multipliers method and convex and linear programming techniques.

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The Linear Programming Formulation,ite or infinite optimization horizon—some references are given in §6.6. The preferred techniques, on the other hand, include the Lagrange multipliers method and convex and linear programming techniques.

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