This 2nd volume of a 2-volume set explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. It introduces myopic optimal policies, Markov decision processes, generalizations of MDPs and related computational considerations, monotone optimal policies, and sequential games. 1984 edition. Includes 43 figures and 50 tables. Unabridged republication of the edition published by McGraw-Hill Book Company, New York, Volume 2, 1984.
Applied Probability Models with Optimization Applications by Sheldon M. Ross Concise advanced-level introduction to stochastic processes that arise in applied probability. Poisson process, renewal theory, Markov chains, Brownian motion, much more. Problems. References. Bibliography. 1970 edition.
Optimal Control and Estimation by Robert F. Stengel Graduate-level text provides introduction to optimal control theory for stochastic systems, emphasizing application of basic concepts to real problems.
Nonstandard Methods in Stochastic Analysis and Mathematical Physics by Sergio Albeverio, Jens Erik Fenstad, Raphael Høegh-Krohn, Tom Lindstrøm Two-part treatment begins with a self-contained introduction to the subject, followed by applications to stochastic analysis and mathematical physics. "A welcome addition." — Bulletin of the American Mathematical Society. 1986 edition.
Mathematical Programming by Steven Vajda This classic by a well-known expert explores both theory and applications. It focuses on linear programming, in addition to other programming topics, and features numerous worked-out examples and problems. 1961 edition.
