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

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

Publisher: IGI Global
Year: 2011
Tongue: English
Leaves: 445
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Subjects

Intelligence & Semantics;AI & Machine Learning;Computer Science;Computers & Technology;Computer Vision & Pattern Recognition;AI & Machine Learning;Computer Science;Computers & Technology;Artificial Intelligence;Computer Science;New, Used & Rental Textbooks;Specialty Boutique

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