Stochastic Optimal Control: The Discrete-Time Case
About this eBook
Review of the 1978 printing:"Bertsekas and Shreve have written a fine book. The exposition is extremely clear and a helpful introductory chapter provides orientation and a guide to the rather intimidating mass of literature on the subject. Apart from anything else, the book serves as an excellent introduction to the arcane world of analytic sets and other lesser known byways of measure theory."
Mark H. A. Davis, Imperial College, in IEEE Trans. on Automatic Control
Among its special features, the book:
1) Resolves definitively the mathematical issues of discrete-time stochastic optimal control problems, including Borel models, and semi-continuous models
2) Establishes the most general possible theory of finite and infinite horizon stochastic dynamic programming models, through the use of analytic sets and universally measurable policies
3) Develops general frameworks for dynamic programming based on abstract contraction and monotone mappings
4) Provides extensive background on analytic sets, Borel spaces and their probability measures
5) Contains much in depth research not found in any other textbook
About the author
Dimitri Bertsekas is McAffee Professor of Engineering at the Massachusetts Institute of Technology (MIT), and Fulton Professor of Computational Decision Making, at Arizona State University (ASU).
Steven Shreve is Orion Hoch Professor of Mathematical Sciences at the Carnegie Mellon University.
