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A Review of Estimation of Distribution Algorithms and Markov Networks

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Markov Networks in Evolutionary Computation

Part of the book series: Adaptation, Learning, and Optimization ((ALO,volume 14))

Abstract

This chapter reviews some of the popular EDAs based on Markov Networks. It starts by giving introduction to general EDAs and describes the motivation behind their emergence. It then categorises EDAs according to the type of probabilistic models they use (directed model based, undirected model based and common model based) and briefly lists some of the popular EDAs in each categories. It then further focuses on undirected model based EDAs, describes their general workflow and the history, and briefly reviews some of the popular EDAs based on undirected models. It also outlines some of the current research work in this area.

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Authors and Affiliations

  1. Business Modelling and Operational Transformation Practice, BT Innovate & Design, Ipswich, UK

    Siddhartha Shakya

  2. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain

    Roberto Santana

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  1. Siddhartha Shakya
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  2. Roberto Santana
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Correspondence to Siddhartha Shakya .

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Editors and Affiliations

  1. Transformation Practice, BT Innovate & Design, Business Modelling and Operational, Cauldwell Hall Road 172, Ipswich, IP4 5DB, United Kingdom

    Siddhartha Shakya

  2. Intelligent Systems Group, Faculty of Informatics, University of the Basque Country, Boadilla del Monte, San Sebastian, Spain

    Roberto Santana

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Shakya, S., Santana, R. (2012). A Review of Estimation of Distribution Algorithms and Markov Networks. In: Shakya, S., Santana, R. (eds) Markov Networks in Evolutionary Computation. Adaptation, Learning, and Optimization, vol 14. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28900-2_2

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  • DOI: https://doi.org/10.1007/978-3-642-28900-2_2

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