Markov Networks in Evolutionary Computation
Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs). EDAs have arisen as one of the most successful experiences in the application of...
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| Další autoři: | , |
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| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edice: | Adaptation, Learning, and Optimization
14 |
| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
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| Edition sous un autre format: | • Markov Networks in Evolutionary Computation, Texte imprimé, 9783642288999 |
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| 245 | 0 | 0 | |a Markov Networks in Evolutionary Computation |c edited by Siddhartha Shakya, Roberto Santana. |
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Adaptation, Learning, and Optimization |v 14 |x 1867-4534 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a From the content: Probabilistic Graphical Models and Markov Networks A review of Estimation of Distribution Algorithms and Markov networks MOA - Markovian Optimisation Algorithm DEUM - Distribution Estimation Using Markov Networks MN-EDA and the use of clique-based factorisations in EDAs Convergence Theorems of Estimation of Distribution Algorithms Adaptive Evolutionary Algorithm based on a Cliqued Gibbs Sampling over Graphical Markov Model Structure | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs). EDAs have arisen as one of the most successful experiences in the application of machine learning methods in optimization, mainly due to their efficiency to solve complex real-world optimization problems and their suitability for theoretical analysis.This book focuses on the different steps involved in the conception, implementation and application of EDAs that use Markov networks, and undirected models in general. It can serve as a general introduction to EDAs but covers also an important current void in the study of these algorithms by explaining the specificities and benefits of modeling optimization problems by means of undirected probabilistic models. All major developments to date in the progressive introduction of Markov networks based EDAs are reviewed in the book. Hot current research trends and future perspectives in the enhancement and applicability of EDAs are also covered. The contributions included in the book address topics as relevant as the application of probabilistic-based fitness models, the use of belief propagation algorithms in EDAs and the application of Markov network based EDAs to real-world optimization problems. The book should be of interest to researchers and practitioners from areas such as optimization, evolutionary computation, and machine learning | ||
| 700 | 1 | |a Shakya, Siddhartha. |4 edt | |
| 700 | 1 | |a Santana, Roberto, |d 19..-...., |c informaticien. |4 edt | |
| 776 | 0 | |t Markov Networks in Evolutionary Computation |b Texte imprimé |z 9783642288999 | |
| 856 | 4 | |q PDF |u https://doi.org/10.1007/978-3-642-28900-2 |z Accès sur la plateforme de l'éditeur | |
| 856 | 4 | |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-BHX2R7QB-C |z Accès sur la plateforme Istex | |
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