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Markov Networks in Evolutionary Computation (Paperback, 2012 ed.)
Loot Price: R4,228
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Markov Networks in Evolutionary Computation (Paperback, 2012 ed.)
Series: Adaptation, Learning, and Optimization, 14
Expected to ship within 10 - 15 working days
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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.
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