Stochastic Learning and Optimization

A Sensitivity-Based Approach
2007
ISBN: 978-0-387-36787-3
Verlag: Springer US

Buch, Englisch, 566 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 1039 g

Performance optimization is vital in the design and operation of modern engineering systems, including communications, manufacturing, robotics, and logistics. Most engineering systems are too complicated to model, or the system parameters cannot be easily identified, so learning techniques have to be applied.

This is a multi-disciplinary area which has been attracting wide attention across many disciplines. Areas such as perturbation analysis (PA) in discrete event dynamic systems (DEDSs), Markov decision processes (MDPs) in operations research, reinforcement learning (RL) or neuro-dynamic programming (NDP) in computer science, identification and adaptive control (I&AC) in control systems, share the common goal: to make the "best decision" to optimize system performance.

This book provides a unified framework based on a sensitivity point of view. It also introduces new approaches and proposes new research topics within this sensitivity-based framework.

Zielgruppe

Research

Autoren/Hrsg.

Cao, Xi-Ren

Fachgebiete

• Mathematik | Informatik Mathematik Mathematische Analysis Variationsrechnung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Überwachungstechnik
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
• Mathematik | Informatik Mathematik Operations Research Spieltheorie
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Geisteswissenschaften Design Produktdesign, Industriedesign
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Technische Wissenschaften Technik Allgemein Konstruktionslehre und -technik
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik

Inhaltsverzeichnis

Four Disciplines in Learning and Optimization.- Perturbation Analysis.- Learning and Optimization with Perturbation Analysis.- Markov Decision Processes.- Sample-Path-Based Policy Iteration.- Reinforcement Learning.- Adaptive Control Problems as MDPs.- The Event-Based Optimization - A New Approach.- Event-Based Optimization of Markov Systems.- Constructing Sensitivity Formulas.