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Evolutionary Computation 2
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Book Synopsis Evolutionary Algorithms for Solving Multi-Objective Problems by : Carlos Coello Coello
Download or read book Evolutionary Algorithms for Solving Multi-Objective Problems written by Carlos Coello Coello and published by Springer Science & Business Media. This book was released on 2007-08-26 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.
Book Synopsis Evolutionary Computation 2 by : Thomas Baeck
Download or read book Evolutionary Computation 2 written by Thomas Baeck and published by CRC Press. This book was released on 2017-06-29 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary Computation 2: Advanced Algorithms and Operators expands upon the basic ideas underlying evolutionary algorithms. The focus is on fitness evaluation, constraint-handling techniques, population structures, advanced techniques in evolutionary computation, and the implementation of evolutionary algorithms. It is intended to be used by individual researchers and students in the expanding field of evolutionary computation.
Book Synopsis Evolutionary Computation by : Kenneth A. De Jong
Download or read book Evolutionary Computation written by Kenneth A. De Jong and published by MIT Press. This book was released on 2006-02-03 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: A clear and comprehensive introduction to the field of evolutionary computation that takes an integrated approach. Evolutionary computation, the use of evolutionary systems as computational processes for solving complex problems, is a tool used by computer scientists and engineers who want to harness the power of evolution to build useful new artifacts, by biologists interested in developing and testing better models of natural evolutionary systems, and by artificial life scientists for designing and implementing new artificial evolutionary worlds. In this clear and comprehensive introduction to the field, Kenneth De Jong presents an integrated view of the state of the art in evolutionary computation. Although other books have described such particular areas of the field as genetic algorithms, genetic programming, evolution strategies, and evolutionary programming, Evolutionary Computation is noteworthy for considering these systems as specific instances of a more general class of evolutionary algorithms. This useful overview of a fragmented field is suitable for classroom use or as a reference for computer scientists and engineers.
Book Synopsis Evolutionary Computation 1 by : Thomas Baeck
Download or read book Evolutionary Computation 1 written by Thomas Baeck and published by CRC Press. This book was released on 2018-10-03 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Introduction to Evolutionary Computing by : Agoston E. Eiben
Download or read book Introduction to Evolutionary Computing written by Agoston E. Eiben and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Evolutionary Computation for Modeling and Optimization by : Daniel Ashlock
Download or read book Evolutionary Computation for Modeling and Optimization written by Daniel Ashlock and published by Springer Science & Business Media. This book was released on 2006-04-04 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.
Book Synopsis Applications of Evolutionary Computation by : Paul Kaufmann (Computer scientist)
Download or read book Applications of Evolutionary Computation written by Paul Kaufmann (Computer scientist) and published by . This book was released on 2019 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. --
Book Synopsis The Nature of Code by : Daniel Shiffman
Download or read book The Nature of Code written by Daniel Shiffman and published by No Starch Press. This book was released on 2024-09-03 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Evolutionary Optimization Algorithms by : Dan Simon
Download or read book Evolutionary Optimization Algorithms written by Dan Simon and published by John Wiley & Sons. This book was released on 2013-06-13 with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt: A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear but theoretically rigorous understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs including opposition-based learning, artificial fish swarms, bacterial foraging, and many others and discusses their similarities and differences from more well-established EAs Includes chapter-end problems plus a solutions manual available online for instructors Offers simple examples that provide the reader with an intuitive understanding of the theory Features source code for the examples available on the author's website Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.
Book Synopsis Evolutionary Computation with Intelligent Systems by : R.S. Chauhan
Download or read book Evolutionary Computation with Intelligent Systems written by R.S. Chauhan and published by CRC Press. This book was released on 2022-03-29 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on cutting-edge innovations and core theories, principles, and algorithms applicable to a wide area. Real-life applications, case studies, and examples are included along with emerging trends, design, and optimized solutions pivoting around the needs of Society 5.0. Evolutionary Computation with Intelligent Systems: A Multidisciplinary Approach to Society 5.0 provides a holistic view of evolutionary computation techniques including principles, procedures, and future applications with real-life examples. The book comprehensively explains evolutionary computation, design, principles, development trends, and optimization and describes how it can transform the operating context of the organization. It exemplifies the potential of evolutionary computation for the next generation and the role of cloud computing in shaping Society 5.0. It also provides insight into various platforms, paradigms, techniques, and tools used in diverse fields. This book appeals to a variety of readers such as academicians, researchers, research scholars, and postgraduates.
Book Synopsis Towards a New Evolutionary Computation by : Jose A. Lozano
Download or read book Towards a New Evolutionary Computation written by Jose A. Lozano and published by Springer. This book was released on 2006-01-21 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimation of Distribution Algorithms (EDAs) are a set of algorithms in the Evolutionary Computation (EC) field characterized by the use of explicit probability distributions in optimization. Contrarily to other EC techniques such as the broadly known Genetic Algorithms (GAs) in EDAs, the crossover and mutation operators are substituted by the sampling of a distribution previously learnt from the selected individuals. EDAs have experienced a high development that has transformed them into an established discipline within the EC field. This book attracts the interest of new researchers in the EC field as well as in other optimization disciplines, and that it becomes a reference for all of us working on this topic. The twelve chapters of this book can be divided into those that endeavor to set a sound theoretical basis for EDAs, those that broaden the methodology of EDAs and finally those that have an applied objective.
Book Synopsis Evolutionary Algorithms by : William M. Spears
Download or read book Evolutionary Algorithms written by William M. Spears and published by Springer Science & Business Media. This book was released on 2000-06-15 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite decades of work in evolutionary algorithms, there remains an uncertainty as to the relative benefits and detriments of using recombination or mutation. This book provides a characterization of the roles that recombination and mutation play in evolutionary algorithms. It integrates important prior work and introduces new theoretical techniques for studying evolutionary algorithms. Consequences of the theory are explored and a novel method for comparing search and optimization algorithms is introduced. The focus allows the book to bridge multiple communities, including evolutionary biologists and population geneticists.
Book Synopsis Evolutionary Algorithms by : Alain Petrowski
Download or read book Evolutionary Algorithms written by Alain Petrowski and published by John Wiley & Sons. This book was released on 2017-04-24 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Parallel Problem Solving from Nature-PPSN VI by : Marc Schoenauer
Download or read book Parallel Problem Solving from Nature-PPSN VI written by Marc Schoenauer and published by Springer Science & Business Media. This book was released on 2000-09-06 with total page 920 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Parallel Problem Solving from Nature, PPSN VI, held in Paris, France in September 2000. The 87 revised full papers presented together with two invited papers were carefully reviewed and selected from 168 submissions. The presentations are organized in topical sections on analysis and theory of evolutionary algorithms, genetic programming, scheduling, representations and operators, co-evolution, constraint handling techniques, noisy and non-stationary environments, combinatorial optimization, applications, machine learning and classifier systems, new algorithms and metaphors, and multiobjective optimization.
Book Synopsis Estimation of Distribution Algorithms by : Pedro Larrañaga
Download or read book Estimation of Distribution Algorithms written by Pedro Larrañaga and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation is devoted to a new paradigm for evolutionary computation, named estimation of distribution algorithms (EDAs). This new class of algorithms generalizes genetic algorithms by replacing the crossover and mutation operators with learning and sampling from the probability distribution of the best individuals of the population at each iteration of the algorithm. Working in such a way, the relationships between the variables involved in the problem domain are explicitly and effectively captured and exploited. This text constitutes the first compilation and review of the techniques and applications of this new tool for performing evolutionary computation. Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation is clearly divided into three parts. Part I is dedicated to the foundations of EDAs. In this part, after introducing some probabilistic graphical models - Bayesian and Gaussian networks - a review of existing EDA approaches is presented, as well as some new methods based on more flexible probabilistic graphical models. A mathematical modeling of discrete EDAs is also presented. Part II covers several applications of EDAs in some classical optimization problems: the travelling salesman problem, the job scheduling problem, and the knapsack problem. EDAs are also applied to the optimization of some well-known combinatorial and continuous functions. Part III presents the application of EDAs to solve some problems that arise in the machine learning field: feature subset selection, feature weighting in K-NN classifiers, rule induction, partial abductive inference in Bayesian networks, partitional clustering, and the search for optimal weights in artificial neural networks. Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation is a useful and interesting tool for researchers working in the field of evolutionary computation and for engineers who face real-world optimization problems. This book may also be used by graduate students and researchers in computer science. `... I urge those who are interested in EDAs to study this well-crafted book today.' David E. Goldberg, University of Illinois Champaign-Urbana.
Book Synopsis Practical Applications of Evolutionary Computation to Financial Engineering by : Hitoshi Iba
Download or read book Practical Applications of Evolutionary Computation to Financial Engineering written by Hitoshi Iba and published by Springer Science & Business Media. This book was released on 2012-02-15 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within. The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.
Book Synopsis Evolutionary Multi-Criterion Optimization by : Carlos M. Fonseca
Download or read book Evolutionary Multi-Criterion Optimization written by Carlos M. Fonseca and published by Springer Science & Business Media. This book was released on 2003-04-07 with total page 825 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Conference on Evolutionary Multi-Criterion Optimization, EMO 2003, held in Faro, Portugal, in April 2003. The 56 revised full papers presented were carefully reviewed and selected from a total of 100 submissions. The papers are organized in topical sections on objective handling and problem decomposition, algorithm improvements, online adaptation, problem construction, performance analysis and comparison, alternative methods, implementation, and applications.
