0
Your cart

Your cart is empty

Books > Business & Economics > Economics > Econometrics

Buy Now

Markov Networks in Evolutionary Computation (Hardcover, 2012 ed.) Loot Price: R4,103
Discovery Miles 41 030
Markov Networks in Evolutionary Computation (Hardcover, 2012 ed.): Siddhartha Shakya, Roberto Santana

Markov Networks in Evolutionary Computation (Hardcover, 2012 ed.)

Siddhartha Shakya, Roberto Santana

Series: Adaptation, Learning, and Optimization, 14

 (sign in to rate)
Loot Price R4,103 Discovery Miles 41 030 | Repayment Terms: R375 pm x 12*

Bookmark and Share

Expected to ship within 7 - 11 working days

Add a Casual Day Sticker for R20

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.

General

Imprint: Springer-Verlag
Country of origin: Germany
Series: Adaptation, Learning, and Optimization, 14
Release date: April 2012
First published: 2012
Editors: Siddhartha Shakya • Roberto Santana
Dimensions: 235 x 155 x 15mm (L x W x T)
Format: Hardcover
Pages: 244
Edition: 2012 ed.
ISBN-13: 978-3-642-28899-9
Categories: Books > Business & Economics > Economics > Econometrics > General
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 3-642-28899-5
Barcode: 9783642288999

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!

Partners