£108.01

Springer EVOLVE: Probability and Evolutionary Computation 447

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Description

EVOLVE provides a strong theoretical foundation for analyzing the behavior of evolutionary algorithms. This volume serves as a bridge between probability, set-oriented numerics, and evolutionary computation, offering researchers and students a deep look into these connected fields. This book presents a collection of 12 thoroughly refereed papers organized into chapters. Each paper is well-structured and maintains a consistent style, making it easy to navigate complex transdisciplinary topics. By combining theoretical findings with optimization problems, this work offers new perspectives on computational intelligence. Whether you are studying computer science or working in AI and machine learning, this text delivers high-quality research on useful and interesting topics. It is an essential resource for those looking to understand the mathematical and computational links between set-oriented numerics and evolutionary processes.

Key Features

Provides strong theoretical support for analyzing evolutionary algorithm behavior and performance.

Acts as a bridge connecting probability, set-oriented numerics, and evolutionary computation.

Contains 12 thoroughly refereed research papers presented in a clear chapter format.

Offers new perspectives through a combination of theoretical findings and optimization problems.

Features well-structured research on useful and interesting transdisciplinary topics.

Part of the Studies in Computational Intelligence series, volume 447.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
15 October 2014
Listed Since
16 October 2014

Barcode

No barcode data available

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