Probabilistic graphical models in artificial intelligence

Larrañaga Múgica, Pedro María and Moral Callejón, Serafín (2011). Probabilistic graphical models in artificial intelligence. "Applied Soft Computing", v. 11 (n. 2); pp. 1511-1528. ISSN 1568-4946. https://doi.org/10.1016/j.asoc.2008.01.003.

Description

Title: Probabilistic graphical models in artificial intelligence
Author/s:
  • Larrañaga Múgica, Pedro María
  • Moral Callejón, Serafín
Item Type: Article
Título de Revista/Publicación: Applied Soft Computing
Date: March 2011
ISSN: 1568-4946
Volume: 11
Subjects:
Freetext Keywords: Probability, Uncertain reasoning, Bayesian networks, Gaussian networks, Credal networks, Factor graphs, Kikuchi approximations, Decision-making, Classification, Optimization, Metaheuristics, Genomic, Forensic
Faculty: Facultad de Informática (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In this paper, we review the role of probabilistic graphical models in artificial intelligence. We start by giving an account of the early years when there was important controversy about the suitability of probability for intelligent systems. We then discuss the main milestones for the foundations of graphical models starting with Pearl’s pioneering work. Some of the main techniques for problem solving (abduction, classification, and decision-making) are briefly explained. Finally, we propose some important challenges for future research and highlight relevant applications (forensic reasoning, genomics and the use of graphical models as a general optimization tool).

Funding Projects

Type
Code
Acronym
Leader
Title
Government of Spain
TIN2004-06204-C03-02
Unspecified
Unspecified
Unspecified
Government of Spain
TIN2005-03824
Unspecified
Unspecified
Unspecified
Government of Spain
CSD2007-00018
Unspecified
Unspecified
Unspecified

More information

Item ID: 72868
DC Identifier: https://oa.upm.es/72868/
OAI Identifier: oai:oa.upm.es:72868
DOI: 10.1016/j.asoc.2008.01.003
Official URL: https://www.sciencedirect.com/science/article/pii/...
Deposited by: Biblioteca Facultad de Informatica
Deposited on: 17 Mar 2023 11:21
Last Modified: 17 Mar 2023 11:21
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