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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.
Title: | Probabilistic graphical models in artificial intelligence |
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Author/s: |
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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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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).
Item ID: | 72868 |
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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 |