Evolutionary Computation: Theory and Applications - Hardcover

 
9789810223069: Evolutionary Computation: Theory and Applications

Synopsis

Evolutionary computation is the study of computational systems which use ideas and get inspiration from natural evolution and adaptation. This book is devoted to the theory and application of evolutionary computation. It is a self-contained volume which covers both introductory material and selected advanced topics. The book can roughly be divided into two major parts: the introductory one and the one on selected advanced topics. Each part consists of several chapters which present an in-depth discussion of selected topics. A strong connection is established between evolutionary algorithms and traditional search algorithms. This connection enables us to incorporate ideas in more established fields into evolutionary algorithms. The book is aimed at a wide range of readers. It does not require previous exposure to the field since introductory material is included. It will be of interest to anyone who is interested in adaptive optimization and learning. People in computer science, artificial intelligence, operations research, and various engineering fields will find it particularly interesting.

"synopsis" may belong to another edition of this title.

Synopsis

Evolutionary computation is the study of computational systems which use ideas and get inspirations from natural evolution and adaptation. This book is devoted to the theory and applications of evolutionary computation. It is a self-contained volume which covers both introductory material and selected advanced topics. The book can be divided into four major parts: introduction, theory, evolutionary optimisation, and evolutionary learning. Each part consists of several chapters which present an in-depth discussion of selected topics. The emphasis of this book is on problem solving techniques. A strong connection is established between evolutionary algorithms and traditional search algorithms. This connection has enabled us to incorporate many good ideas in more established fields into evolutionary algorithms so that we are not reinventing wheels. The book is aimed at a wide range of readers. It does not require previous exposure to the field of evolutionary computation since introductory material is included. It should be of interest to anyone who is interested in adaptive optimization and learning.

People in computer science, operations research, and most engineering fields should find it of interest.

"About this title" may belong to another edition of this title.