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Evolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems and into leading-edge scientific research. Spatially structured EAs have different properties than standard, mixing EAs. By virtue of the structured disposition of the population members they bring about new dynamical features that can be harnessed to solve difficult problems faster and more efficiently. This book describes the state of the art in spatially structured EAs by using graph concepts as a unifying theme. The models, their analysis, and their empirical behavior are presented in detail. Moreover, there is new material on non-standard networked population structures such as small-world networks. The book should be of interest to advanced undergraduate and graduate students working in evolutionary computation, machine learning, and optimization. It should also be useful to researchers and professionals working in fields where the topological structures of populations and their evolution plays a role.
Computer science. --- Computer programming. --- Computers. --- Algorithms. --- Numerical analysis. --- Artificial intelligence. --- Computer Science. --- Programming Techniques. --- Artificial Intelligence (incl. Robotics). --- Theory of Computation. --- Computation by Abstract Devices. --- Algorithm Analysis and Problem Complexity. --- Numeric Computing. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Mathematical analysis --- Algorism --- Algebra --- Arithmetic --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Computers --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Informatics --- Science --- Foundations --- Programming --- Evolutionary programming (Computer science) --- Evolutionary computation. --- Computation, Evolutionary --- Neural networks (Computer science) --- Computer programming --- Information theory. --- Computer software. --- Electronic data processing. --- Artificial Intelligence. --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Office practice --- Software, Computer --- Communication theory --- Communication --- Automation --- Computer algorithms. --- Mathematical optimization. --- Numerical Analysis.
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Complex analysis --- Discrete mathematics --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- discrete wiskunde --- complexe analyse (wiskunde) --- informatica --- robots --- numerieke analyse
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evolutionary algorithms --- Genetic Algorithms --- cellular automata --- Biology --- neural networks
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The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.
Artificial intelligence. --- Mathematical optimization. --- Engineering. --- Operations research. --- Information theory. --- Artificial Intelligence. --- Optimization. --- Computational Intelligence. --- Operations Research/Decision Theory. --- Theory of Computation. --- Communication theory --- Communication --- Cybernetics --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Construction --- Industrial arts --- Technology --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Fifth generation computers --- Neural computers --- Computational intelligence. --- Decision making. --- Computers. --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Calculators --- Cyberspace --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Decision making --- Computational complexity. --- Complexity, Computational --- Computer science. --- Operations Research and Decision Theory. --- Informatics --- Science
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Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically.This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as
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The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.
Numerical methods of optimisation --- Operational research. Game theory --- Mathematical control systems --- Mathematical statistics --- Applied physical engineering --- Planning (firm) --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- neuronale netwerken --- fuzzy logic --- cybernetica --- toegepaste informatica --- automatisering --- mathematische modellen --- speltheorie --- econometrie --- wiskunde --- KI (kunstmatige intelligentie) --- operationeel onderzoek --- ingenieurswetenschappen --- informatietheorie --- AI (artificiële intelligentie)
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Evolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems and into leading-edge scientific research. Spatially structured EAs have different properties than standard, mixing EAs. By virtue of the structured disposition of the population members they bring about new dynamical features that can be harnessed to solve difficult problems faster and more efficiently. This book describes the state of the art in spatially structured EAs by using graph concepts as a unifying theme. The models, their analysis, and their empirical behavior are presented in detail. Moreover, there is new material on non-standard networked population structures such as small-world networks. The book should be of interest to advanced undergraduate and graduate students working in evolutionary computation, machine learning, and optimization. It should also be useful to researchers and professionals working in fields where the topological structures of populations and their evolution plays a role.
Complex analysis --- Discrete mathematics --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- discrete wiskunde --- complexe analyse (wiskunde) --- informatica --- robots --- numerieke analyse
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The book constitutes the refereed proceedings of the 11th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2013, held in Lausanne, Switzerland, in April 2013. The 51 revised full papers presented were carefully reviewed and selected from a total of 91 submissions. The papers are organized in topical sections on neural networks, evolutionary computation, soft computing, bioinformatics and computational biology, advanced computing, and applications.
Computer science. --- Computer software. --- Artificial intelligence. --- Optical pattern recognition. --- Bioinformatics. --- Computer Science. --- Computation by Abstract Devices. --- Algorithm Analysis and Problem Complexity. --- Pattern Recognition. --- Computational Biology/Bioinformatics. --- Artificial Intelligence (incl. Robotics). --- Computer algorithms --- Adaptive computing systems --- Natural computation --- Engineering & Applied Sciences --- Computer Science --- Biologically-inspired computing --- Bio-inspired computing --- Natural computing --- Adaptive computing --- Configurable computing systems --- Reconfigurable computing systems --- Bio-informatics --- Biological informatics --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Software, Computer --- Informatics --- Nature-inspired algorithms --- Computers. --- Algorithms. --- Pattern recognition. --- Bionics --- Electronic data processing --- Computer systems --- Artificial Intelligence. --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Biology --- Information science --- Computational biology --- Systems biology --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Science --- Data processing --- Vino - Analisi --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Algorism --- Algebra --- Arithmetic --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Cybernetics --- Calculators --- Cyberspace --- Foundations --- Pattern recognition systems. --- Theory of Computation. --- Automated Pattern Recognition. --- Computational and Systems Biology. --- Pattern classification systems --- Pattern recognition computers --- Computer vision
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Chacun peut observer dans le monde réel l'omniprésence de systèmes complexex constitués de nombreux éléments en interaction et dont les caractéristiques globales ne peuvent se réduire à celles de leurs composants: ce sont par exemple les cellules d'un organisme vivant, les colonies de fourmis, les écosystèmes, ou encore les systèmes économiques, l'Internet et les réseaux sociaux. Dans le futur, nos sociétés devront relever l'immense défi scientifique et technologique qui consiste à comprendre ces systèmes pour les adapter, les contrôler et les modéliser.Au travers d'exemples choisis sans complication inutile, les auteurs proposent une introduction par la pratique aux système complexes. Leur méthode repose sur la conviction que toute compréhension suppose un acte d'expérience; l'ouvrage est composé d'ateliers où il s'agit de simuler une dynamique collective à partir de sa modélisation orientée-agent.Les étudiants, les enseignants, les créateurs et plus largement toute personne avide de développer sa culture et d'actualiser ses connaissances tireront parti de cet ouvrage pluridisciplinaire accessible à un large public.
Systèmes, Théorie des Simulation, Méthode de --- Modèles mathématiques --- Réseaux sociaux (Internet) --- Modèles écologiques --- Réseaux neuronaux (informatique) --- Ingénierie des systèmes --- Systèmes informatiques --- System theory --- Simulation methods --- Mathematical models --- Online social networks --- Neural networks --- Systems engineering
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Complex analysis --- Mathematical statistics --- Biology --- Computer science --- Programming --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- factoranalyse --- complexe analyse (wiskunde) --- biologie --- informatica --- programmeren (informatica) --- KI (kunstmatige intelligentie) --- robots --- AI (artificiële intelligentie)
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