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Stochastic Learning and Optimization

A Sensitivity-Based Approach

Springer US,
Buch
197,94 € Lieferbar in 5-7 Tagen
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Kurzbeschreibung

Performance optimization is vital in the design and operation of modern engineering systems. This book provides a unified framework based on a sensitivity point of view. It introduces new approaches and proposes new research topics.

Details
Schlagworte
Hauptbeschreibung

Titel: Stochastic Learning and Optimization
Autoren/Herausgeber: Xi-Ren Cao
Ausgabe: 2007

ISBN/EAN: 9780387367873

Seitenzahl: 566
Format: 23,5 x 15,5 cm
Produktform: Hardcover/Gebunden
Gewicht: 1,040 g
Sprache: Englisch

Stochastic learning and optimization is a multidisciplinary subject that has wide applications in modern engineering, social, and financial problems, including those in Internet and wireless communications, manufacturing, robotics, logistics, biomedical systems, and investment science.  This book is unique in the following aspects.
(Four areas in one book)  This book covers various disciplines in learning and optimization, including perturbation analysis (PA) of discrete-event dynamic systems, Markov decision processes (MDP)s), reinforcement learning (RL), and adaptive control, within a unified framework.
(A simple approach to MDPs) This book introduces MDP theory through a simple approach based on performance difference formulas.  This approach leads to results for the n-bias optimality with long-run average-cost criteria and Blackwell's optimality without discounting.
(Event-based optimization) This book introduces the recently developed event-based optimization approach, which opens up a research direction in overcoming or alleviating the difficulties due to the curse of dimensionality issue by utilizing the system's special features.
(Sample-path construction) This book emphasizes physical interpretations based on the sample-path construction.

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