Table of contents
About this book
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.
stochastic control decentralized stochastic control quantization numerical approximation finite state approximations Markov decision processes asymptotic optimality
- DOI https://doi.org/10.1007/978-3-319-79033-6
- Copyright Information Springer International Publishing AG, part of Springer Nature 2018
- Publisher Name Birkhäuser, Cham
- eBook Packages Mathematics and Statistics
- Print ISBN 978-3-319-79032-9
- Online ISBN 978-3-319-79033-6
- Series Print ISSN 2324-9749
- Series Online ISSN 2324-9757
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