Probabilistic graphical models and Markov networks

Roberto Santana, Siddhartha Shakya

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

Abstract

This chapter introduces probabilistic graphical models and explain their use for modelling probabilistic relationships between variables in the context of optimisation with EDAs.We focus on Markov networksmodels and review different algorithms used to learn and sample Markov networks. Other probabilistic graphical models are also reviewed and their differences with Markov networks are analysed.

Original languageBritish English
Title of host publicationMarkov Networks in Evolutionary Computation
PublisherSpringer Verlag
Pages3-19
Number of pages17
Edition1
ISBN (Print)9783642288999
DOIs
StatePublished - 2012

Publication series

NameAdaptation, Learning, and Optimization
Number1
Volume14
ISSN (Print)1867-4534
ISSN (Electronic)1867-4542

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