Asymptotic properties and optimization of some non-Markovian stochastic processes

Evgueni I. Gordienko; Antonio Garcia; Juan Ruiz de Chavez

Displaying similar documents to “Asymptotic properties and optimization of some non-Markovian stochastic processes”

Estimates of stability of Markov control processes with unbounded costs

Evgueni I. Gordienko, Francisco Salem-Silva (2000)

Kybernetika

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For a discrete-time Markov control process with the transition probability $p$ , we compare the total discounted costs $V_{β}$ $(π_{β})$ and $V_{β} ({\tilde{π}}_{β})$ , when applying the optimal control policy $π_{β}$ and its approximation ${\tilde{π}}_{β}$ . The policy ${\tilde{π}}_{β}$ is optimal for an approximating process with the transition probability $\tilde{p}$ . A cost per stage for considered processes can be unbounded. Under certain ergodicity assumptions we establish the upper bound for the relative stability index $[V_{β} ({\tilde{π}}_{β}) - V_{β} (π_{β})] / V_{β} (π_{β})$ . This bound does not depend...

Partially observable Markov decision processes with partially observable random discount factors

E. Everardo Martinez-Garcia, J. Adolfo Minjárez-Sosa, Oscar Vega-Amaya (2022)

Kybernetika

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This paper deals with a class of partially observable discounted Markov decision processes defined on Borel state and action spaces, under unbounded one-stage cost. The discount rate is a stochastic process evolving according to a difference equation, which is also assumed to be partially observable. Introducing a suitable control model and filtering processes, we prove the existence of optimal control policies. In addition, we illustrate our results in a class of GI/GI/1 queueing systems...

Asymptotic stability condition for stochastic Markovian systems of differential equations

Efraim Shmerling (2010)

Mathematica Bohemica

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Asymptotic stability of the zero solution for stochastic jump parameter systems of differential equations given by $d X (t) = A (ξ (t)) X (t) d t + H (ξ (t)) X (t) d w (t)$ , where $ξ (t)$ is a finite-valued Markov process and w(t) is a standard Wiener process, is considered. It is proved that the existence of a unique positive solution of the system of coupled Lyapunov matrix equations derived in the paper is a necessary asymptotic stability condition.

A mathematical framework for learning and adaption: (generalized) random systems with complete connections.

Ulrich Herkenrath, Radu Theodorescu (1981)

Trabajos de Estadística e Investigación Operativa

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The aim of this paper is to show that the theory of (generalized) random systems with complete connection may serve as a mathematical framework for learning and adaption. Chapter 1 is of an introductory nature and gives a general description of the problems with which one is faced. In Chapter 2 the mathematical model and some results about it are explained. Chapter 3 deals with special learning and adaption models.

On some recent aspects of stochastic control and their applications.

Pham, Huyên (2005)

Probability Surveys [electronic only]

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