Additional information is available at the publisher’s
web site www.wiley.com/mathematics
ISBN 0-471-33052-3
Further Information James C. Spall
Johns Hopkins University
Applied Physics Laboratory
11100 Johns Hopkins Rd.
Laurel, MD 20723-6099
USA
From the
back cover...
Stochastic search and optimization techniques are
used in a vast number of areas, including aerospace, medicine, transportation,
and finance, to name but a few. Whether the goal is refining the
design of a missile or aircraft, determining the effectiveness of
a new drug, developing the most efficient timing strategies for
traffic signals, or making investment decisions in order to increase
profits, stochastic algorithms can help researchers and practitioners
devise optimal solutions to countless real-world problems.
Introduction to Stochastic Search and Optimization:
Estimation, Simulation, and Control is a graduate-level introduction
to the principles, algorithms, and practical aspects of stochastic
optimization, including applications drawn from engineering, statistics,
and computer science. The treatment is both rigorous and broadly
accessible, distinguishing this text from much of the current literature
and providing students, researchers, and practitioners with a strong
foundation for the often-daunting task of solving real-world problems.
The text covers a broad range of today’s most widely used stochastic
algorithms, including:
Random search
Machine
(reinforcement) learning
Recursive
linear estimation
Model
selection
Stochastic
approximation
Simulation-based
optimization
Simulated
annealing
Markov
chain Monte Carlo
Genetic
and evolutionary algorithms
Optimal experimental design
The book includes over 130 examples, Web links
to software and data sets, more than 250 exercises for the reader,
and an extensive list of references. These features help make the
text an invaluable resource for those interested in the theory or
practice of stochastic search and optimization.
James C. Spall is a member of the Principal
Professional Staff at The Johns Hopkins University, Applied Physics
Laboratory, and is the Chair of the Applied and Computational Mathematics
Program within the Johns Hopkins School of Engineering. Dr. Spall
has published extensively in the areas of control and statistics
and holds two U.S. patents. Among other appointments, he is a Senior
Editor for the IEEE Transactions on Automatic Control and a Contributing Editor for the Current Index to Statistics.
Dr. Spall has received numerous research and publications awards
and is an elected Fellow of the Institute of Electrical and Electronics
Engineers (IEEE).