Introduction to Stochastic Search and Optimization. Estimation, Simulation, and Control (Spall, J.C.

This comprehensive book offers 504 main pages divided into 17 chapters. In addition, five very useful and clearly written appendices are provided, covering multivariate analysis, basic tests in statistics, probability theory and convergence, random number generators and Markov processes. Some of the topics covered in the book include: stochastic approximation in nonlinear search and optimization; evolutionary computations; reinforcement learning via temporal differences; mathematical model selection; and computer-simulation-based optimizations. Over 250 exercises are provided in the book, though only a small number of them have solutions included in the volume. A separate solution manual is available, as is a very informative webpage. The book may serve as either a reference for researchers and practitioners in many fields or as an excellent graduate level textbook.