Evolutionary Computation Theory And Applications

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Evolutionary Computation: Theory and Applications

Author : Xin Yao
Publisher : World Scientific
Page : 376 pages
File Size : 53,7 Mb
Release : 1999-11-22
Category : Computers
ISBN : 9789814518161

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Evolutionary Computation: Theory and Applications by Xin Yao Pdf

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. Contents:Introduction (X Yao)Evolutionary Computation in Behavior Engineering (M Colombetti & M Dorigo)A General Method for Incremental Self-Improvement and Multi-Agent Learning (J Schmidhuber)Teacher: A Genetics-Based System for Learning and for Generalizing Heuristics (B W Wah & A Ieumwananonthachai)Automatic Discovery of Protein Motifs Using Genetic Programming (J R Koza & D Andre)The Role of Self Organization in Evolutionary Computations (A C Tsoi & J Shaw)Virus-Evolutionary Genetic Algorithm and Its Application to Traveling Salesman Problem (T Fukuda et al.)Hybrid Evolutionary Optimization Algorithm for Constrained Problems (J-H Kim & H Myung)CAM-BRAIN — The Evolutionary Engineering of a Billion Neuron Artificial Brain (H de Garis)An Evolutionary Approach to the N-Player Iterated Prisoner's Dilemma Game (X Yao & Darwen) Readership: Graduate students, practitioners and researchers in engineering and electronics and computer science. keywords:Genetic Algorithms;Evolutionary Computation;Evolutionary Algorithms;Genetic Programming;Evolutionary Robotics;Global Optimization;Evolutionary Games;Global Optimization;Machine Learning;Artificial Intelligence

Advances in Evolutionary Computing

Author : Ashish Ghosh,Shigeyoshi Tsutsui
Publisher : Springer Science & Business Media
Page : 1001 pages
File Size : 52,9 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642189654

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Advances in Evolutionary Computing by Ashish Ghosh,Shigeyoshi Tsutsui Pdf

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.

Evolutionary Algorithms and Neural Networks

Author : Seyedali Mirjalili
Publisher : Springer
Page : 156 pages
File Size : 55,7 Mb
Release : 2018-06-26
Category : Technology & Engineering
ISBN : 9783319930251

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Evolutionary Algorithms and Neural Networks by Seyedali Mirjalili Pdf

This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.

Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation

Author : Samuelson Hong, Wei-Chiang
Publisher : IGI Global
Page : 357 pages
File Size : 42,8 Mb
Release : 2013-03-31
Category : Computers
ISBN : 9781466636293

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Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation by Samuelson Hong, Wei-Chiang Pdf

Evolutionary computation has emerged as a major topic in the scientific community as many of its techniques have successfully been applied to solve problems in a wide variety of fields. Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation provides comprehensive research on emerging theories and its aspects on intelligent computation. Particularly focusing on breaking trends in evolutionary computing, algorithms, and programming, this publication serves to support professionals, government employees, policy and decision makers, as well as students in this scientific field.

Theory of Evolutionary Computation

Author : Benjamin Doerr,Frank Neumann
Publisher : Springer Nature
Page : 506 pages
File Size : 51,6 Mb
Release : 2019-11-20
Category : Computers
ISBN : 9783030294144

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Theory of Evolutionary Computation by Benjamin Doerr,Frank Neumann Pdf

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.

Genetic and Evolutionary Computation

Author : Stephen L. Smith,Stefano Cagnoni
Publisher : John Wiley & Sons
Page : 249 pages
File Size : 43,9 Mb
Release : 2011-07-26
Category : Science
ISBN : 9781119956785

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Genetic and Evolutionary Computation by Stephen L. Smith,Stefano Cagnoni Pdf

Genetic and Evolutionary Computation: Medical Applications provides an overview of the range of GEC techniques being applied to medicine and healthcare in a context that is relevant not only for existing GEC practitioners but also those from other disciplines, particularly health professionals. There is rapidly increasing interest in applying evolutionary computation to problems in medicine, but to date no text that introduces evolutionary computation in a medical context. By explaining the basic introductory theory, typical application areas and detailed implementation in one coherent volume, this book will appeal to a wide audience from software developers to medical scientists. Centred around a set of nine case studies on the application of GEC to different areas of medicine, the book offers an overview of applications of GEC to medicine, describes applications in which GEC is used to analyse medical images and data sets, derive advanced models, and suggest diagnoses and treatments, finally providing hints about possible future advancements of genetic and evolutionary computation in medicine. Explores the rapidly growing area of genetic and evolutionary computation in context of its viable and exciting payoffs in the field of medical applications. Explains the underlying theory, typical applications and detailed implementation. Includes general sections about the applications of GEC to medicine and their expected future developments, as well as specific sections on applications of GEC to medical imaging, analysis of medical data sets, advanced modelling, diagnosis and treatment. Features a wide range of tables, illustrations diagrams and photographs.

Evolutionary Computation for Modeling and Optimization

Author : Daniel Ashlock
Publisher : Springer Science & Business Media
Page : 572 pages
File Size : 48,9 Mb
Release : 2006-04-04
Category : Computers
ISBN : 9780387319094

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Evolutionary Computation for Modeling and Optimization by Daniel Ashlock Pdf

Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.

Introduction to Evolutionary Computing

Author : Agoston E. Eiben,J.E. Smith
Publisher : Springer Science & Business Media
Page : 307 pages
File Size : 54,5 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9783662050941

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Introduction to Evolutionary Computing by Agoston E. Eiben,J.E. Smith Pdf

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.

Evolutionary Computation

Author : Ashish M. Gujarathi,B. V. Babu
Publisher : CRC Press
Page : 652 pages
File Size : 41,7 Mb
Release : 2016-12-01
Category : Computers
ISBN : 9781315342160

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Evolutionary Computation by Ashish M. Gujarathi,B. V. Babu Pdf

Edited by professionals with years of experience, this book provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applications. Covering both the theory and applications of evolutionary computation, the book offers exhaustive coverage of several topics on nontraditional evolutionary techniques, details working principles of new and popular evolutionary algorithms, and discusses case studies on both scientific and real-world applications of optimization

Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques

Author : Chis, Monica
Publisher : IGI Global
Page : 282 pages
File Size : 45,8 Mb
Release : 2010-06-30
Category : Education
ISBN : 9781615208104

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Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques by Chis, Monica Pdf

Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques lays the foundation for the successful integration of evolutionary computation into software engineering. It surveys techniques ranging from genetic algorithms, to swarm optimization theory, to ant colony optimization, demonstrating their uses and capabilities. These techniques are applied to aspects of software engineering such as software testing, quality assessment, reliability assessment, and fault prediction models, among others, to providing researchers, scholars and students with the knowledge needed to expand this burgeoning application.

Applications of Evolutionary Computation

Author : Paul Kaufmann (Computer scientist),Pedro A. Castillo
Publisher : Unknown
Page : 642 pages
File Size : 44,8 Mb
Release : 2019
Category : Evolutionary computation
ISBN : 3030166937

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Applications of Evolutionary Computation by Paul Kaufmann (Computer scientist),Pedro A. Castillo Pdf

This book constitutes the refereed proceedings of the 22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held in Leipzig, Germany, in April 2019, co-located with the Evo*2019 events EuroGP, EvoCOP and EvoMUSART. The 44 revised full papers presented were carefully reviewed and selected from 66 submissions. They were organized in topical sections named: Engineering and Real World Applications; Games; General; Image and Signal Processing; Life Sciences; Networks and Distributed Systems; Neuroevolution and Data Analytics; Numerical Optimization: Theory, Benchmarks, and Applications; Robotics. --

Evolutionary Intelligence

Author : S. Sumathi,T. Hamsapriya,P. Surekha
Publisher : Springer Science & Business Media
Page : 600 pages
File Size : 44,5 Mb
Release : 2008-05-15
Category : Technology & Engineering
ISBN : 9783540753827

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Evolutionary Intelligence by S. Sumathi,T. Hamsapriya,P. Surekha Pdf

This book provides a highly accessible introduction to evolutionary computation. It details basic concepts, highlights several applications of evolutionary computation, and includes solved problems using MATLAB software and C/C++. This book also outlines some ideas on when genetic algorithms and genetic programming should be used. The most difficult part of using a genetic algorithm is how to encode the population, and the author discusses various ways to do this.

Evolutionary Algorithms in Engineering Applications

Author : Dipankar Dasgupta,Zbigniew Michalewicz
Publisher : Springer Science & Business Media
Page : 561 pages
File Size : 50,5 Mb
Release : 2013-06-29
Category : Computers
ISBN : 9783662034231

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Evolutionary Algorithms in Engineering Applications by Dipankar Dasgupta,Zbigniew Michalewicz Pdf

Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering. It will be useful for engineers, designers, developers, and researchers in any scientific discipline interested in the applications of evolutionary algorithms. The volume consists of five parts, each with four or five chapters. The topics are chosen to emphasize application areas in different fields of engineering. Each chapter can be used for self-study or as a reference by practitioners to help them apply evolutionary algorithms to problems in their engineering domains.

Applications of Evolutionary Computation

Author : Stephen Smith
Publisher : Springer Nature
Page : 422 pages
File Size : 55,5 Mb
Release : 2024-06-28
Category : Electronic
ISBN : 9783031568558

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Applications of Evolutionary Computation by Stephen Smith Pdf

Applications of Evolutionary Computing

Author : Stefano Cagnoni,Jens Gottlieb,Emma Hart,Martin Middendorf,Günther R. Raidl
Publisher : Springer
Page : 346 pages
File Size : 53,9 Mb
Release : 2003-07-31
Category : Computers
ISBN : 9783540460046

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Applications of Evolutionary Computing by Stefano Cagnoni,Jens Gottlieb,Emma Hart,Martin Middendorf,Günther R. Raidl Pdf

This book constitutes the refereed proceedings of three workshops on the application of evolutionary programming and algorithms in various domains; these workshops were held in conjunction with the 5th European Conference on Genetic Programming, EuroGP 2002, in Kinsale, Ireland, in April 2002. The 33 revised full papers presented were carefully reviewed and selected by the respective program committees. In accordance with the three workshops EvoCOP, EvoIASP, and EvoSTIM/EvoPLAN, the papers are organized in topical sections on combinatorial optimization problems; image analysis and signal processing; and scheduling, timetabling, and AI planning.