In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized shastic 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 shastic control problems.
This volume is perfect for researchers and graduate students interested in shastic 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.
1133188288
This volume is perfect for researchers and graduate students interested in shastic 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.
Finite Approximations in Discrete-Time Stochastic Control: Quantized Models and Asymptotic Optimality
In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized shastic 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 shastic control problems.
This volume is perfect for researchers and graduate students interested in shastic 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.
This volume is perfect for researchers and graduate students interested in shastic 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.
69.99
In Stock
5
1
Finite Approximations in Discrete-Time Stochastic Control: Quantized Models and Asymptotic Optimality
198
Finite Approximations in Discrete-Time Stochastic Control: Quantized Models and Asymptotic Optimality
198Paperback(Softcover reprint of the original 1st ed. 2018)
$69.99
69.99
In Stock
Product Details
| ISBN-13: | 9783030077105 |
|---|---|
| Publisher: | Springer International Publishing |
| Publication date: | 01/09/2019 |
| Series: | Systems & Control: Foundations & Applications |
| Edition description: | Softcover reprint of the original 1st ed. 2018 |
| Pages: | 198 |
| Product dimensions: | 6.10(w) x 9.25(h) x 0.02(d) |
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