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A review on probabilistic graphical models in evolutionary computation

Larrañaga Múgica , Pedro and Karshenas, Hossein and Bielza Lozoya, Maria Concepcion and Santana, Roberto (2012) A review on probabilistic graphical models in evolutionary computation. Journal of Heuristics, 18 (5). 795 - 819. ISSN 1381-1231

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Item Type:Article
Creators NameCreators email (if known)
Larrañaga Múgica , Pedro
Karshenas, Hossein
Bielza Lozoya, Maria Concepcion
Santana, Roberto
Title:A review on probabilistic graphical models in evolutionary computation
Publisher:Springer Verlag
Journal/Publication Title:Journal of Heuristics
Date:August 2012
Department:Artificial intelligence
Faculty:Computer Faculty (UPM)
Creative Commons licenses:Recognition - No derivative works - No commercial
Item ID:15826
Subjects:Robotics and Industrial Computer

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Official URL: http://www.springer.com/?SGWID=5-102-0-0-0


Thanks to their inherent properties, probabilistic graphical models are one of the prime candidates for machine learning and decision making tasks especially in uncertain domains. Their capabilities, like representation, inference and learning, if used effectively, can greatly help to build intelligent systems that are able to act accordingly in different problem domains. Evolutionary algorithms is one such discipline that has employed probabilistic graphical models to improve the search for optimal solutions in complex problems. This paper shows how probabilistic graphical models have been used in evolutionary algorithms to improve their performance in solving complex problems. Specifically, we give a survey of probabilistic model building-based evolutionary algorithms, called estimation of distribution algorithms, and compare different methods for probabilistic modeling in these algorithms.

Item Type:Article
Uncontrolled Keywords:Probabilistic graphical model, Bayesian network, Evolutionary computation, Estimation of distribution algorithm, Modelo gráfico porbabilístico, red Bayesiana, Computación evolutiva.
Subjects:Robotics and Industrial Computer
Código ID:15826
Depositado Por:Memoria Investigacion
Depositado el:18 Jun 2013 16:08
Last Modified:26 Aug 2013 00:56

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