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Decision Theory Models for Applications in Artificial Intelligence: Concepts and
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Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions Hardcover - 2011 - 1st Edition

by L. Enrique Sucar (Editor); Eduardo F. Morales (Editor); Jesse Hoey (Editor)


From the publisher

One of the goals of artificial intelligence (AI) is creating autonomous agents that must make decisions based on uncertain and incomplete information. The goal is to design rational agents that must take the best action given the information available and their goals. Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions provides an introduction to different types of decision theory techniques, including MDPs, POMDPs, Influence Diagrams, and Reinforcement Learning, and illustrates their application in artificial intelligence. This book provides insights into the advantages and challenges of using decision theory models for developing intelligent systems.

Details

  • Title Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions
  • Author L. Enrique Sucar (Editor); Eduardo F. Morales (Editor); Jesse Hoey (Editor)
  • Binding Hardcover
  • Edition number 1st
  • Edition 1
  • Pages 446
  • Volumes 1
  • Language ENG
  • Publisher Information Science Reference
  • Date 2011-10-01
  • Features Bibliography, Index, Table of Contents
  • ISBN 9781609601652 / 1609601653
  • Weight 2.9 lbs (1.32 kg)
  • Dimensions 11.2 x 8.6 x 1.1 in (28.45 x 21.84 x 2.79 cm)
  • Library of Congress Catalog Number 2010054421
  • Dewey Decimal Code 006.3
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Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions
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Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions

by L. Enrique Sucar, L. Enrique Sucar, Eduardo F. Morales, Jesse Hoey

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Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions
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Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions

by Sucar, L. Enrique (Editor)/ Morales, Eduardo F. (Editor)/ Hoey, Jesse (Editor)

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Information Science Reference, 2011. Hardcover. New. 1st edition. 444 pages. 11.25x8.50x1.05 inches.
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