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Theoretical Aspects Of Evolutionary Computing

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Theoretical Aspects Of Evolutionary Computing

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Author : Leila Kallel
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Theoretical Aspects Of Evolutionary Computing written by Leila Kallel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Computers categories.

During the first week of September 1999, the Second EvoNet Summer School on Theoretical Aspects of Evolutionary Computing was held at the Middelheim cam pus of the University of Antwerp, Belgium. Originally intended as a small get together of PhD students interested in the theory of evolutionary computing, the summer school grew to become a successful combination of a four-day workshop with over twenty researchers in the field and a two-day lecture series open to a wider audience. This book is based on the lectures and workshop contributions of this summer school. Its first part consists of tutorial papers which introduce the reader to a num ber of important directions in the theory of evolutionary computing. The tutorials are at graduate level andassume only a basic backgroundin mathematics and com puter science. No prior knowledge ofevolutionary computing or its theory is nec essary. The second part of the book consists of technical papers, selected from the workshop contributions. A number of them build on the material of the tutorials, exploring the theory to research level. Other technical papers may require a visit to the library.

Theoretical Aspects Of Evolutionary Computing

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Author : Leila Kallel
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-05-08

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 It combines this with recent, previously unpublished research papers based on the material of the tutorials.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.

Advances In Evolutionary Computing

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Author : Ashish Ghosh
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-11-26

Advances In Evolutionary Computing written by Ashish Ghosh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-11-26 with Computers categories.

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.

Introduction To Evolutionary Computing

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Author : A.E. Eiben
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-06

Introduction To Evolutionary Computing written by A.E. Eiben and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-06 with Computers categories.

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.

Advances In Evolutionary Computing

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Author : Ashish Ghosh
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

The term evolutionary computing refers to the study of the foundations and applications of certain heuristic techniques based on the principles of natural evolution; thus the aim of designing evolutionary algorithms (EAs) is to mimic some of the processes taking place in natural evolution. These algo rithms are classified into three main categories, depending more on historical development than on major functional techniques. In fact, their biological basis is essentially the same. Hence EC = GA uGP u ES uEP EC = Evolutionary Computing GA = Genetic Algorithms,GP = Genetic Programming ES = Evolution Strategies,EP = Evolutionary Programming Although the details of biological evolution are not completely understood (even nowadays), there is some strong experimental evidence to support the following points: • Evolution is a process operating on chromosomes rather than on organ isms. • Natural selection is the mechanism that selects organisms which are well adapted to the environment toreproduce more often than those which are not. • The evolutionary process takes place during the reproduction stage that includes mutation (which causes the chromosomes of offspring to be dif ferent from those of the parents) and recombination (which combines the chromosomes of the parents to produce the offspring). Based upon these features, the previously mentioned three models of evolutionary computing were independently (and almost simultaneously) de veloped. An evolutionary algorithm (EA) is an iterative and stochastic process that operates on a set of individuals (called a population).

Evolutionary Multiobjective Optimization

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Author : Ajith Abraham
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-04-22

Evolutionary Multiobjective Optimization written by Ajith Abraham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-04-22 with Computers categories.

Evolutionary Multiobjective Optimization is a rare collection of the latest state-of-the-art theoretical research, design challenges and applications in the field of multiobjective optimization paradigms using evolutionary algorithms. It includes two introductory chapters giving all the fundamental definitions, several complex test functions and a practical problem involving the multiobjective optimization of space structures under static and seismic loading conditions used to illustrate the various multiobjective optimization concepts. Important features include: Detailed overview of all the multiobjective optimization paradigms using evolutionary algorithms Excellent coverage of timely, advanced multiobjective optimization topics State-of-the-art theoretical research and application developments Chapters authored by pioneers in the field Academics and industrial scientists as well as engineers engaged in research, development and application of evolutionary algorithm based Multiobjective Optimization will find the comprehensive coverage of this book invaluable.

The Nature Of Code

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Author : Daniel Shiffman
language : en
Publisher: No Starch Press
Release Date : 2024-09-03

The Nature Of Code written by Daniel Shiffman and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-03 with Computers categories.

All aboard The Coding Train! This beginner-friendly creative coding tutorial is designed to grow your skills in a fun, hands-on way as you build simulations of real-world phenomena with “The Coding Train” YouTube star Daniel Shiffman. What if you could re-create the awe-inspiring flocking patterns of birds or the hypnotic dance of fireflies—with code? For over a decade, The Nature of Code has empowered countless readers to do just that, bridging the gap between creative expression and programming. This innovative guide by Daniel Shiffman, creator of the beloved Coding Train, welcomes budding and seasoned programmers alike into a world where code meets playful creativity. This JavaScript-based edition of Shiffman’s groundbreaking work gently unfolds the mysteries of the natural world, turning complex topics like genetic algorithms, physics-based simulations, and neural networks into accessible and visually stunning creations. Embark on this extraordinary adventure with projects involving: A physics engine: Simulate the push and pull of gravitational attraction. Flocking birds: Choreograph the mesmerizing dance of a flock. Branching trees: Grow lifelike and organic tree structures. Neural networks: Craft intelligent systems that learn and adapt. Cellular automata: Uncover the magic of self-organizing patterns. Evolutionary algorithms: Play witness to natural selection in your code. Shiffman’s work has transformed thousands of curious minds into creators, breaking down barriers between science, art, and technology, and inviting readers to see code not just as a tool for tasks but as a canvas for boundless creativity. Whether you’re deciphering the elegant patterns of natural phenomena or crafting your own digital ecosystems, Shiffman’s guidance is sure to inform and inspire. The Nature of Code is not just about coding; it’s about looking at the natural world in a new way and letting its wonders inspire your next creation. Dive in and discover the joy of turning code into art—all while mastering coding fundamentals along the way. NOTE: All examples are written with p5.js, a JavaScript library for creative coding, and are available on the book's website.

The Theory Of Evolution Strategies

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Author : Hans-Georg Beyer
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-03-27

The Theory Of Evolution Strategies written by Hans-Georg Beyer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-03-27 with Computers categories.

Evolutionary Algorithms, in particular Evolution Strategies, Genetic Algorithms, or Evolutionary Programming, have found wide acceptance as robust optimization algorithms in the last ten years. Compared with the broad propagation and the resulting practical prosperity in different scientific fields, the theory has not progressed as much. This monograph provides the framework and the first steps toward the theoretical analysis of Evolution Strategies (ES). The main emphasis is on understanding the functioning of these probabilistic optimization algorithms in real-valued search spaces by investigating the dynamical properties of some well-established ES algorithms. The book introduces the basic concepts of this analysis, such as progress rate, quality gain, and self-adaptation response, and describes how to calculate these quantities. Based on the analysis, functioning principles are derived, aiming at a qualitative understanding of why and how ES algorithms work.

Evolutionary Computation For Modeling And Optimization

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Author : Daniel Ashlock
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-04

Evolutionary Computation For Modeling And Optimization written by Daniel Ashlock and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-04 with Computers categories.

Evolutionary Computation for Optimization and Modeling is an introduction to evolutionary computation, a field which includes genetic algorithms, evolutionary programming, evolution strategies, and genetic programming. The text is a survey of some application of evolutionary algorithms. It introduces mutation, crossover, design issues of selection and replacement methods, the issue of populations size, and the question of design of the fitness function. It also includes a methodological material on efficient implementation. Some of the other topics in this book include the design of simple evolutionary algorithms, applications to several types of optimization, evolutionary robotics, simple evolutionary neural computation, and several types of automatic programming including genetic programming. The book gives applications to biology and bioinformatics and introduces a number of tools that can be used in biological modeling, including evolutionary game theory. Advanced techniques such as cellular encoding, grammar based encoding, and graph based evolutionary algorithms are also covered. This book presents a large number of homework problems, projects, and experiments, with a goal of illustrating single aspects of evolutionary computation and comparing different methods. Its readership is intended for an undergraduate or first-year graduate course in evolutionary computation for computer science, engineering, or other computational science students. Engineering, computer science, and applied math students will find this book a useful guide to using evolutionary algorithms as a problem solving tool.

Evolutionary Computation

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Author : Xin Yao
language : en
Publisher: World Scientific
Release Date : 1999

Evolutionary Computation written by Xin Yao and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Science categories.

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.

Theoretical Aspects Of Evolutionary Computing

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