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Introduction

  • Luis Enrique SucarEmail author
Chapter
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Abstract

This introductory chapter starts by describing the effects of uncertainty in intelligent systems and presents a brief history of the development of uncertain reasoning in artificial intelligence. Then it presents the basic approach for probabilistic reasoning, motivating the development of probabilistic graphical models. It gives an overview of probabilistic graphical models, the types of models, and how these can be classified. It concludes with a description of the rest of the book.

Keywords

Bayesian Network Joint Probability Markov Decision Process Markov Random Field Marginal Probability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE)Santa María TonantzintlaMexico

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