Limiting discounted-cost control of partially observable stochastic systems
Title | Limiting discounted-cost control of partially observable stochastic systems PDF eBook |
Author | Jesús Barreiro Hurlé |
Publisher | |
Pages | 20 |
Release | 1999 |
Genre | |
ISBN |
Limiting Discounted-cost Control of Partially Observable Stochastic Systems
Title | Limiting Discounted-cost Control of Partially Observable Stochastic Systems PDF eBook |
Author | Onésimo Hernández-Lerma |
Publisher | |
Pages | 20 |
Release | 1999 |
Genre | |
ISBN |
Optimization, Control, and Applications of Stochastic Systems
Title | Optimization, Control, and Applications of Stochastic Systems PDF eBook |
Author | Daniel Hernández-Hernández |
Publisher | Springer Science & Business Media |
Pages | 331 |
Release | 2012-08-15 |
Genre | Science |
ISBN | 0817683372 |
This volume provides a general overview of discrete- and continuous-time Markov control processes and stochastic games, along with a look at the range of applications of stochastic control and some of its recent theoretical developments. These topics include various aspects of dynamic programming, approximation algorithms, and infinite-dimensional linear programming. In all, the work comprises 18 carefully selected papers written by experts in their respective fields. Optimization, Control, and Applications of Stochastic Systems will be a valuable resource for all practitioners, researchers, and professionals in applied mathematics and operations research who work in the areas of stochastic control, mathematical finance, queueing theory, and inventory systems. It may also serve as a supplemental text for graduate courses in optimal control and dynamic games.
Finite Approximations in Discrete-Time Stochastic Control
Title | Finite Approximations in Discrete-Time Stochastic Control PDF eBook |
Author | Naci Saldi |
Publisher | Birkhäuser |
Pages | 196 |
Release | 2018-05-11 |
Genre | Mathematics |
ISBN | 3319790331 |
In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems. This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original models and the methods are general enough that researchers can build corresponding approximation results, typically with no additional assumptions.
SIAM Journal on Control and Optimization
Title | SIAM Journal on Control and Optimization PDF eBook |
Author | Society for Industrial and Applied Mathematics |
Publisher | |
Pages | 804 |
Release | 2007 |
Genre | Control theory |
ISBN |
Stochastic Control of Partially Observable Systems
Title | Stochastic Control of Partially Observable Systems PDF eBook |
Author | Alain Bensoussan |
Publisher | Cambridge University Press |
Pages | 364 |
Release | 1992-08-13 |
Genre | Mathematics |
ISBN | 052135403X |
These systems play an important role in many applications.
Measure-Valued Processes in the Control of Partially-Observable Stochastic Systems
Title | Measure-Valued Processes in the Control of Partially-Observable Stochastic Systems PDF eBook |
Author | Wendell H. Fleming |
Publisher | |
Pages | 30 |
Release | 1979 |
Genre | |
ISBN |
This paper is concerned with the optimal control of continuous-time Markov processes. The admissible control laws are based on white-noise corrupted observations of a function on the state processes. A 'separated' control problem is introduced, whose states are probability measures on the original state space. The original and separated control problems are related via the nonlinear filter equation. The existence of a minimum for the separated problem is established. Under more restrictive assumptions it is shown that the minimum expected cost for the separated problem equals the infimum of expected costs for the original problem with partially observed states.