£107.98

Springer Scalable Optimization via Probabilistic Modeling Book

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Description

Explore the cutting edge of evolutionary computation with Scalable Optimization via Probabilistic Modeling. This volume from the Studies in Computational Intelligence series focuses on estimation of distribution algorithms (EDAs), a technique driving breakthroughs in genetic and evolutionary computation. As optimization becomes more complex, understanding these probabilistic models is essential for researchers and professionals in computer science. This book provides a comprehensive summary of the current state of the art while identifying future directions for the field. It is designed for those seeking to master the latest developments in optimization and machine learning techniques. Whether you are building a professional library or studying advanced algorithms, this text offers the technical depth needed to understand how EDAs are transforming the landscape of computational intelligence.

Key Features

Focuses on estimation of distribution algorithms (EDAs) to understand their role in modern evolutionary computation.

Provides a detailed summary of the current state of the art in scalable optimization techniques.

Identifies future trends and directions for the field of probabilistic modeling and optimization.

Part of the Studies in Computational Intelligence series (Volume 33) for academic and professional use.

https://www.amazon.co.uk/dp/B07D38CY1Q?tag=tosheroon-21

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
30 November 2010
Listed Since
20 September 2010

Barcode

No barcode data available

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