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Powell, Warren B.

Optimal Learning

Powell, Warren B. - Optimal Learning, ebook

114,60€

Ebook, ePUB with Adobe DRM
ISBN: 9781118309841
DRM Restrictions

Printing121 pages with an additional page accrued every 6 hours, capped at 121 pages
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Learn the science of collecting information to make effective decisions

Everyday decisions are made without the benefit of accurate information. Optimal Learning develops the needed principles for gathering information to make decisions, especially when collecting information is time-consuming and expensive. Designed for readers with an elementary background in probability and statistics, the book presents effective and practical policies illustrated in a wide range of applications, from energy, homeland security, and transportation to engineering, health, and business.

This book covers the fundamental dimensions of a learning problem and presents a simple method for testing and comparing policies for learning. Special attention is given to the knowledge gradient policy and its use with a wide range of belief models, including lookup table and parametric and for online and offline problems. Three sections develop ideas with increasing levels of sophistication:

  • Fundamentals explores fundamental topics, including adaptive learning, ranking and selection, the knowledge gradient, and bandit problems
  • Extensions and Applications features coverage of linear belief models, subset selection models, scalar function optimization, optimal bidding, and stopping problems
  • Advanced Topics explores complex methods including simulation optimization, active learning in mathematical programming, and optimal continuous measurements

Each chapter identifies a specific learning problem, presents the related, practical algorithms for implementation, and concludes with numerous exercises. A related website features additional applications and downloadable software, including MATLAB and the Optimal Learning Calculator, a spreadsheet-based package that provides an introduc­tion to learning and a variety of policies for learning.

Keywords: Probability & Mathematical Statistics, biosurveillance, biomedical research, stochastic optimization, resource allocation problems, Markov decision processes, dynamic programming, algorithmic strategies, math programming, linear programming, nonlinear programming, integer programming, learning algorithms

Author(s)
 
Publisher
John Wiley and Sons, Inc.
Publication year
2012
Language
en
Edition
1
Series
Wiley Series in Probability and Statistics
Page amount
416 pages
Category
Natural Sciences
Format
Ebook
eISBN (ePUB)
9781118309841
Printed ISBN
9780470596692

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