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Cellular Genetic Algorithms

Author: Enrique Alba

Publisher: Springer Science & Business Media

Published: 2009-04-05

Total Pages: 251

ISBN-13: 0387776109

Cellular Genetic Algorithms defines a new class of optimization algorithms based on the concepts of structured populations and Genetic Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book with equal and parallel emphasis on both theory and practice. This book is a key source for studying and designing cellular GAs, as well as a self-contained primary reference book for these algorithms.

Genetic Algorithms and Machine Learning for Programmers

Author: Frances Buontempo

Publisher: Pragmatic Bookshelf

Published: 2019-01-23

Total Pages: 307

ISBN-13: 1680506587

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Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you. Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems. In this book, you will: Use heuristics and design fitness functions. Build genetic algorithms. Make nature-inspired swarms with ants, bees and particles. Create Monte Carlo simulations. Investigate cellular automata. Find minima and maxima, using hill climbing and simulated annealing. Try selection methods, including tournament and roulette wheels. Learn about heuristics, fitness functions, metrics, and clusters. Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon. What You Need: Code in C++ (>= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions.

An Introduction to Genetic Algorithms

Author: Melanie Mitchell

Publisher: MIT Press

Published: 1998-03-02

Total Pages: 226

ISBN-13: 9780262631853

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Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.

Evolutionary Computation in Combinatorial Optimization

Author: Jens Gottlieb

Publisher: Springer Science & Business Media

Published: 2004-03-26

Total Pages: 252

ISBN-13: 3540213678

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This book constitutes the refereed proceedings for the 4th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2004, held in Coimbra, Portugal, in April together with EuroGP 2004 and six workshops on evolutionary computing. The 23 revised full papers presented were carefully reviewed and selected from 86 submissions. Among the topics addressed are evolutionary algorithms as well as metaheuristics like memetic algorithms, ant colony optimization, and scatter search; the papers are dealing with representations, operators, search spaces, adaptation, comparison of algorithms, hybridization of different methods, and theory. Among the combinatorial optimization problems studied are graph coloring, network design, cutting, packing, scheduling, timetabling, traveling salesman, vehicle routing, and various other real-world applications.

Evolutionary Multi-criterion Optimization

Author: Eckart Zitzler

Publisher: Springer Science & Business Media

Published: 2001-02-28

Total Pages: 725

ISBN-13: 3540417451

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This book constitutes the refereed proceedings of the First International Conference on Multi-Criterion Optimization, EMO 2001, held in Zurich, Switzerland in March 2001. The 45 revised full papers presented were carefully reviewed and selected from a total of 87 submissions. Also included are two tutorial surveys and two invited papers. The book is organized in topical sections on algorithm improvements, performance assessment and comparison, constraint handling and problem decomposition, uncertainty and noise, hybrid and alternative methods, scheduling, and applications of multi-objective optimization in a variety of fields.

Parallel Problem Solving from Nature-PPSN VI

Author: Marc Schoenauer

Publisher: Springer Science & Business Media

Published: 2000-09-06

Total Pages: 920

ISBN-13: 3540410562

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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.

Theory of Practical Cellular Automaton

Author: Xuewei Li

Publisher: Springer

Published: 2018-05-17

Total Pages: 352

ISBN-13: 9811074976

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This book addresses the intellectual foundations, function, modeling approaches and complexity of cellular automata; explores cellular automata in combination with genetic algorithms, neural networks and agents; and discusses the applications of cellular automata in economics, traffic and the spread of disease. Pursuing a blended approach between knowledge and philosophy, it assigns equal value to methods and applications.

Non-Standard Computation

Author: Tino Gramß

Publisher: Wiley-VCH

Published: 1998-07-08

Total Pages: 252

ISBN-13:

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There's never enough computer power for challenging questions. Problems such as the design of turbines consisting of more than 100 parts or the simulation of systems of some 50 interacting particles are far beyond today's computer capacities. Or, how to find the shortest phone line connecting 100 given cities? The most promising answers to such questions come from unconventional technologies. The massive parallelism of molecular computers or the ingenious use of quantum systems by universal quantum computers provide solutions to the dilemma. And as for the phone line problem - genetic algorithms mimick the way nature found its way from the first cells to today's creatures. While relying on conventional computer hardware, they introduce an element of chance on the software level, thus circumventing the disadvantages of traditional deterministic algorithms. A textbook for those shaping the future of computing, this volume is also pure fun.

Parallel Problem Solving from Nature - PPSN X

Author: Günter Rudolph

Publisher: Springer

Published: 2008-09-16

Total Pages: 1183

ISBN-13: 3540877002

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This book constitutes the refereed proceedings of the 10th International Conference on Parallel Problem Solving from Nature, PPSN 2008, held in Dortmund, Germany, in September 2008. The 114 revised full papers presented were carefully reviewed and selected from 206 submissions. The conference covers a wide range of topics, such as evolutionary computation, quantum computation, molecular computation, neural computation, artificial life, swarm intelligence, artificial ant systems, artificial immune systems, self-organizing systems, emergent behaviors, and applications to real-world problems. The paper are organized in topical sections on formal theory, new techniques, experimental analysis, multiobjective optimization, hybrid methods, and applications.

Advances In Dynamics, Instrumentation And Control - Proceedings Of The 2004 International Conference (Cdic '04)

Author: Chun-yi Su

Publisher: World Scientific

Published: 2004-10-18

Total Pages: 515

ISBN-13: 9814481491

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This volume is a compilation of 50 articles representing the scientific and technical advances in various aspects of system dynamics, instrumentation, measurement techniques, and control. It serves as an important resource in the field. The topics include state-of-the-art contributions in the fields of dynamics and control of nonlinear, hybrid, stochastic, time-delayed and piecewise affine systems; nonlinear control theory; control of chaotic systems; adaptive, model predictive and real-time controls, with applications involving vehicular systems, fault diagnostics, and flexible and cellular manufacturing systems, vibration suppression, biomedical, mobile robots, etc.The proceedings have been selected for coverage in:• Index to Scientific & Technical Proceedings® (ISTP® / ISI Proceedings)• Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)• CC Proceedings — Engineering & Physical Sciences