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.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!