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Global Optimization with the Gaussian Polytree EDA [chapter]

Ignacio Segovia Domínguez, Arturo Hernández Aguirre, Enrique Villa Diharce
2011 Lecture Notes in Computer Science  
The proposed Gaussian polytree estimation of distribution algorithm is applied to a set of benchmark functions. The experimental results show that the approach is robust, comparisons are provided.  ...  The variables are assumed to be Gaussian.  ...  The goal of this paper is to introduce the polytree for continuous variables, that is, a polytree in continuous domain with Gaussian variables and its application to EDAs for optimization.  ... 
doi:10.1007/978-3-642-25330-0_15 fatcat:ddk6l7geavbgpmkcce5yiicvc4

Estimation of distribution algorithms based on copula functions

Rogelio Salinas-Gutiérrez, Arturo Hernández-Aguirre, Enrique R. Villa-Diharce
2011 Proceedings of the 13th annual conference companion on Genetic and evolutionary computation - GECCO '11  
My brother Edgar Iván and my mom Martha deserve special thanks for giving my wife and my children all the assistance they needed during the last year in Aguascalientes.  ...  Thanks to these supports, I will return to my job at the Universidad Autónoma de Aguascalientes with a strong academic preparation for teaching and doing research.  ...  The solid line is used for the EDAs based on copula selection and the dashed line for the EDAs based on the Gaussian copula.  ... 
doi:10.1145/2001858.2002094 dblp:conf/gecco/Salinas-GutierrezAD11a fatcat:deuqz6tsbze25lsimrc6ny4h7m

Incorporating Regular Vines in Estimation of Distribution Algorithms [chapter]

Rogelio Salinas-Gutiérrez, Arturo Hernández-Aguirre, Enrique R. Villa-Diharce
2013 Studies in Computational Intelligence  
This work presents a procedure for selecting the most important dependencies in EDAs by truncating regular vines.  ...  This chapter presents the incorporation and use of regular vines into Estimation of Distribution Algorithms for solving numerical optimization problems.  ...  Center for Research in Mathematics.  ... 
doi:10.1007/978-3-642-32726-1_2 fatcat:2msakluycfcilnosf6auqq4l4a

Probabilistic graphical models in artificial intelligence

P. Larrañaga, S. Moral
2011 Applied Soft Computing  
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). #  ...  We then discuss the main milestones for the foundations of graphical models starting with Pearl's pioneering work.  ...  Acknowledgments The authors are very grateful to the anonymous reviewers who provided some valuable and useful suggestions.  ... 
doi:10.1016/j.asoc.2008.01.003 fatcat:y25eqeaj5rfrrjwb5nuxcwiqzm

Learning Bayesian networks: approaches and issues

Rónán Daly, Qiang Shen, Stuart Aitken
2011 Knowledge engineering review (Print)  
This article is not intended to be a tutorial-for this, there are many books on the topic, which will be presented.  ...  These ideas are fundamental to the theory of Bayesian networks and will enable a better understanding of the context of the subject.  ...  Stuart Aitken is funded by BBSRC grant BB/F015976/1, and by the Centre for Systems Biology at Edinburgh, a Centre for Integrative Systems Biology (CISB) funded by BBSRC and EPSRC, reference BB/ D019621  ... 
doi:10.1017/s0269888910000251 fatcat:schmhrymdjewrggsdq7vmx23uu

A survey on optimization metaheuristics

Ilhem Boussaïd, Julien Lepagnot, Patrick Siarry
2013 Information Sciences  
Metaheuristics are widely recognized as efficient approache s for many hard optimization problems. This paper provides a survey of some of the main metaheuristics.  ...  The purpose of this paper is to present a global overview of the main metaheuristics and their principles. That attempt of survey on metaheu ristics is structured in the following way.  ...  The research community, the number of sessions, workshops, and conferences dealing with metaheurist ics is growing significantly.  ... 
doi:10.1016/j.ins.2013.02.041 fatcat:osz7frllkrfqfke4crydwr4pe4

Structure Learning for Directed Trees

Martin E. Jakobsen, Rajen D. Shah, Peter Bühlmann, Jonas Peters
2022
The Gaussian polytree eda with copula functions and mutations. In EVOLVE-A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation, pages 123–153.  ...  A simple approach for finding the globally optimal Bayesian network structure. In Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence, pages 445–452.  ... 
doi:10.3929/ethz-b-000553211 fatcat:i2orztdn5zdd3e366uvj4h43vi

Integration of symbolic and connectionist AI techniques in the development of Decision Support Systems applied to biochemical processes

Davide Sottara, Mello, Paola Mello
2010 unpublished
There exist complex systems, such as bio-chemical plants, which require a constant management to be kept in optimal operating conditions.  ...  Since different techniques are more suitable for different problems, a complex management infrastructure is likely to include more than one module.  ...  (w|T ) becomes Gaussian as well.  ... 
fatcat:t2ybirxfprbrjfqprhabpqulny