Parallel Problem Solving From Nature Ppsn X

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Parallel Problem Solving From Nature Ppsn X

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Author : Günter Rudolph
language : en
Publisher: Springer
Release Date : 2008-09-16

Parallel Problem Solving From Nature Ppsn X written by Günter Rudolph and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-16 with Computers categories.

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.

Hypervolume Based Search For Multiobjective Optimization

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Author : Johannes M. Bader
language : en
Publisher: Johannes Bader
Release Date : 2010-02-13

Hypervolume Based Search For Multiobjective Optimization written by Johannes M. Bader and has been published by Johannes Bader this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-13 with Computers categories.

Most problems encountered in practice involve the optimization of multiple criteria. Usually, some of them are conflicting such that no single solution is simultaneously optimal with respect to all criteria, but instead many incomparable compromise solutions exist. In recent years, evidence has accumulated showing that Evolutionary Algorithms (EAs) are effective means of finding good approximate solutions to such problems. One of the crucial parts of EAs consists of repeatedly selecting suitable solutions. In this process, the two key issues are as follows: first, a solution that is better than another solution in all objectives should be preferred over the latter. Second, the diversity of solutions should be supported, whereby often user preference dictates what constitutes a good diversity.The hypervolume offers one possibility to achieve the two aspects; for this reason, it has been gaining increasing importance in recent years. The present thesis investigates three central topics of the hypervolume that are still unsolved:1: Although more and more EAs use the hypervolume as selection criterion, the resulting distribution of points favored by the hypervolume has scarcely been investigated so far. Many studies only speculate about this question, and in parts contradict one another.2: The computational load of the hypervolume calculation sharply increases the more criteria are considered. This hindered so far the application of the hypervolume to problems with more than about five criteria.3: Often a crucial aspect is to maximize the robustness of solutions, which is characterized by how far the properties of a solution can degenerate when implemented in practice. So far, no attempt has been made to consider robustness of solutions within hypervolume-based search.

Machine Learning For Evolution Strategies

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Author : Oliver Kramer
language : en
Publisher: Springer
Release Date : 2016-05-25

Machine Learning For Evolution Strategies written by Oliver Kramer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-25 with Technology & Engineering categories.

This book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strategies. The set of methods comprises covariance matrix estimation, meta-modeling of fitness and constraint functions, dimensionality reduction for search and visualization of high-dimensional optimization processes, and clustering-based niching. After giving an introduction to evolution strategies and machine learning, the book builds the bridge between both worlds with an algorithmic and experimental perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python using the machine learning library scikit-learn. The examples are conducted on typical benchmark problems illustrating algorithmic concepts and their experimental behavior. The book closes with a discussion of related lines of research.

Multimodal Optimization By Means Of Evolutionary Algorithms

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Author : Mike Preuss
language : en
Publisher: Springer
Release Date : 2015-11-27

Multimodal Optimization By Means Of Evolutionary Algorithms written by Mike Preuss and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-27 with Computers categories.

This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.

Contemporary Evolution Strategies

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Author : Thomas Bäck
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-10-02

Contemporary Evolution Strategies written by Thomas Bäck 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 2013-10-02 with Computers categories.

This book surveys key algorithm developments between 1990 and 2012, with brief descriptions, a unified pseudocode for each algorithm and downloadable program code. Provides a taxonomy to clarify similarities and differences as well as historical relationships.

Theory And Principled Methods For The Design Of Metaheuristics

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Author : Yossi Borenstein
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-19

Theory And Principled Methods For The Design Of Metaheuristics written by Yossi Borenstein 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 2013-12-19 with Computers categories.

Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.

Handbook On Computer Learning And Intelligence In 2 Volumes

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Author : Plamen Parvanov Angelov
language : en
Publisher: World Scientific
Release Date : 2022-06-29

Handbook On Computer Learning And Intelligence In 2 Volumes written by Plamen Parvanov Angelov and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-29 with Computers categories.

The Handbook on Computer Learning and Intelligence is a second edition which aims to be a one-stop-shop for the various aspects of the broad research area of computer learning and intelligence. This field of research evolved so much in the last five years that it necessitates this new edition of the earlier Handbook on Computational Intelligence.This two-volume handbook is divided into five parts. Volume 1 covers Explainable AI and Supervised Learning. Volume 2 covers three parts: Deep Learning, Intelligent Control, and Evolutionary Computation. The chapters detail the theory, methodology and applications of computer learning and intelligence, and are authored by some of the leading experts in the respective areas. The fifteen core chapters of the previous edition have been written and significantly refreshed by the same authors. Parts of the handbook have evolved to keep pace with the latest developments in computational intelligence in the areas that span across Machine Learning and Artificial Intelligence. The Handbook remains dedicated to applications and engineering-orientated aspects of these areas over abstract theories.Related Link(s)

Handbook Of Heuristics

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Author : Rafael Martí
language : en
Publisher: Springer Nature
Release Date : 2025-11-17

Handbook Of Heuristics written by Rafael Martí and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-17 with Computers categories.

The handbook of heuristics consists of five main parts: search strategies, local search, metaheuristics, analysis and implementations, and applications. They cover from search methods and methodological aspects, such as matheuristics, the exciting field in which mathematical programming is combined with heuristics, to applications that provide the practitioner with a description of some relevant optimization issues in a number of specific application areas, such as scheduling, vehicle routing, or network optimization. The first edition of the Handbook of Heuristics was published in 2018 and contained 47 chapters. In this second edition, the authors revised 30 of them to include new developments in the area that appeared in the last few years. In particular, the reader may find 14 chapters in search strategies, including a new chapter on deep learning, 4 in local search, 14 in metaheuristics, 5 in analysis and implementations, and 24 in applications. The inclusion of 14 new chapters makes this second edition even more comprehensive, totaling 61 chapters.

Theory Of Evolutionary Computation

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Author : Benjamin Doerr
language : en
Publisher: Springer Nature
Release Date : 2019-11-20

Theory Of Evolutionary Computation written by Benjamin Doerr and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Computers categories.

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.

Artificial Life X

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Author : Luis Mateus Rocha
language : en
Publisher: Bradford Book
Release Date : 2006

Artificial Life X written by Luis Mateus Rocha and has been published by Bradford Book this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.

Proceedings from the Tenth International Conference on Artificial Life, marking two decades of interdisciplinary research in this growing scientific community.Artificial Life is an interdisciplinary effort to investigate the fundamental properties of living systems through the simulation and synthesis of life-like processes in artificial media. The field brings a powerful set of tools to the study of how high-level behavior can arise in systems governed by simple rules of interaction.This tenth volume marks two decades of research in this interdisciplinary scientific community, a period marked by vast advances in the life sciences. The field has contributed fundamentally to our understanding of life itself through computer models, and has led to novel solutions to complex real-world problems--from disease prevention to stock market prediction--across high technology and human society. The proceedings of the biennial A-life conference--which has grown over the years from a small workshop in Santa Fe to a major international meeting--reflect the increasing importance of the work to all areas of contemporary science.