Introduction to Stochastic Search and Optimization
Estimation, Simulation, and Control
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A strongly interdisciplinary book with potential and actual applications of the material in branches of mathematics, engineering, science, and social sciences, this reference covers a broad range of the most popular stochastic algorithms, including random search, experimental design methods, stochastic approximation, simulated annealing, genetic and evolutionary methods, and machine learning.
_ Unique in its survey of the range of topics.
_ Contains a strong, interdisciplinary format that will appeal to both students and researchers.
_ Features exercises and web links to software and data sets.
_ Contains a strong, interdisciplinary format that will appeal to both students and researchers.
_ Features exercises and web links to software and data sets.
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