Introduction to Evolutionary Computing PDF Download
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Author: A.E. Eiben
Publisher: Springer Science & Business Media
ISBN: 9783540401841
Category : Computers
Languages : en
Pages : 328
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Book Description
The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.
Author: A.E. Eiben
Publisher: Springer Science & Business Media
ISBN: 9783540401841
Category : Computers
Languages : en
Pages : 328
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Book Description
The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.
Author: Kenneth A. De Jong
Publisher: MIT Press
ISBN: 0262041944
Category : Computers
Languages : en
Pages : 267
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Book Description
This text is an introduction to the field of evolutionary computation. It approaches evolution strategies and genetic programming, as instances of a more general class of evolutionary algorithms.
Author: Thomas Baeck
Publisher: CRC Press
ISBN: 1351989421
Category : Mathematics
Languages : en
Pages : 374
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Book Description
The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.
Author: Benjamin Doerr
Publisher: Springer Nature
ISBN: 3030294145
Category : Computers
Languages : en
Pages : 527
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Book Description
This edited book reports on recent developments in the theory of evolutionary computation, or more generally the domain of randomized search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of randomized search heuristics, followed by three chapters on how to measure the complexity of a search heuristic: black-box complexity, a counterpart of classical complexity theory in black-box optimization; parameterized complexity, aimed at a more fine-grained view of the difficulty of problems; and the fixed-budget perspective, which answers the question of how good a solution will be after investing a certain computational budget. The book then describes theoretical results on three important questions in evolutionary computation: how to profit from changing the parameters during the run of an algorithm; how evolutionary algorithms cope with dynamically changing or stochastic environments; and how population diversity influences performance. Finally, the book looks at three algorithm classes that have only recently become the focus of theoretical work: estimation-of-distribution algorithms; artificial immune systems; and genetic programming. Throughout the book the contributing authors try to develop an understanding for how these methods work, and why they are so successful in many applications. The book will be useful for students and researchers in theoretical computer science and evolutionary computing.
Author: Xin-She Yang
Publisher: Springer
ISBN: 3642296947
Category : Technology & Engineering
Languages : en
Pages : 797
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Book Description
Alan Turing pioneered many research areas such as artificial intelligence, computability, heuristics and pattern formation. Nowadays at the information age, it is hard to imagine how the world would be without computers and the Internet. Without Turing's work, especially the core concept of Turing Machine at the heart of every computer, mobile phone and microchip today, so many things on which we are so dependent would be impossible. 2012 is the Alan Turing year -- a centenary celebration of the life and work of Alan Turing. To celebrate Turing's legacy and follow the footsteps of this brilliant mind, we take this golden opportunity to review the latest developments in areas of artificial intelligence, evolutionary computation and metaheuristics, and all these areas can be traced back to Turing's pioneer work. Topics include Turing test, Turing machine, artificial intelligence, cryptography, software testing, image processing, neural networks, nature-inspired algorithms such as bat algorithm and cuckoo search, and multiobjective optimization and many applications. These reviews and chapters not only provide a timely snapshot of the state-of-art developments, but also provide inspiration for young researchers to carry out potentially ground-breaking research in the active, diverse research areas in artificial intelligence, cryptography, machine learning, evolutionary computation, and nature-inspired metaheuristics. This edited book can serve as a timely reference for graduates, researchers and engineers in artificial intelligence, computer sciences, computational intelligence, soft computing, optimization, and applied sciences.
Author: Daniel Ashlock
Publisher: Springer Science & Business Media
ISBN: 0387319093
Category : Computers
Languages : en
Pages : 578
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Book Description
Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.
Author: Ashish Ghosh
Publisher: Springer Science & Business Media
ISBN: 3642189652
Category : Computers
Languages : en
Pages : 1001
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Book Description
This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems. Around 23 articles deal with various theoretical aspects of EC and 17 articles demonstrate the success of EC methodologies. These articles are written by leading experts of the field from different countries all over the world.
Author: Leila Kallel
Publisher: Springer Science & Business Media
ISBN: 9783540673965
Category : Business & Economics
Languages : en
Pages : 516
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Book Description
This book is the first in the field to provide extensive, entry level tutorials to the theory of Evolutionary Computing, covering the main approaches to understanding the dynamics of Evolutionary Algorithms. It combines this with recent, previously unpublished research papers based on the material of the tutorials. The outcome is a book which is self-contained to a large degree, attractive both to graduate students and researchers from other fields who want to get acquainted with the theory of Evolutionary Computing, and to active researchers in the field who can use this book as a reference and a source of recent results.
Author: Gustavo Olague
Publisher: Springer
ISBN: 3662436930
Category : Computers
Languages : en
Pages : 432
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Book Description
This book explains the theory and application of evolutionary computer vision, a new paradigm where challenging vision problems can be approached using the techniques of evolutionary computing. This methodology achieves excellent results for defining fitness functions and representations for problems by merging evolutionary computation with mathematical optimization to produce automatic creation of emerging visual behaviors. In the first part of the book the author surveys the literature in concise form, defines the relevant terminology, and offers historical and philosophical motivations for the key research problems in the field. For researchers from the computer vision community, he offers a simple introduction to the evolutionary computing paradigm. The second part of the book focuses on implementing evolutionary algorithms that solve given problems using working programs in the major fields of low-, intermediate- and high-level computer vision. This book will be of value to researchers, engineers, and students in the fields of computer vision, evolutionary computing, robotics, biologically inspired mechatronics, electronics engineering, control, and artificial intelligence.
Author: Alain Petrowski
Publisher: John Wiley & Sons
ISBN: 1848218044
Category : Computers
Languages : en
Pages : 260
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Book Description
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms. Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.
