Estimation Of Distribution Algorithms

Author : Pedro Larrañaga,José A. Lozano
Publisher : Springer Science & Business Media
Page : 382 pages
File Size : 53,8 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461515395

Get Book

Estimation of Distribution Algorithms by Pedro Larrañaga,José A. Lozano Pdf

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.

Author : Jose A. Lozano,Pedro Larrañaga,Iñaki Inza,Endika Bengoetxea
Publisher : Springer
Page : 306 pages
File Size : 41,7 Mb
Release : 2006-01-21
Category : Technology & Engineering
ISBN : 9783540324942

Get Book

Towards a New Evolutionary Computation by Jose A. Lozano,Pedro Larrañaga,Iñaki Inza,Endika Bengoetxea Pdf

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.

Author : Benjamin Doerr,Frank Neumann
Publisher : Springer Nature
Page : 506 pages
File Size : 49,7 Mb
Release : 2019-11-20
Category : Computers
ISBN : 9783030294144

Get Book

Theory of Evolutionary Computation by Benjamin Doerr,Frank Neumann Pdf

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.

Author : Bao-Liang Lu,Liqing Zhang,James Kwok
Publisher : Springer Science & Business Media
Page : 799 pages
File Size : 54,7 Mb
Release : 2011-10-26
Category : Computers
ISBN : 9783642249570

Get Book

Neural Information Processing by Bao-Liang Lu,Liqing Zhang,James Kwok Pdf

The three volume set LNCS 7062, LNCS 7063, and LNCS 7064 constitutes the proceedings of the 18th International Conference on Neural Information Processing, ICONIP 2011, held in Shanghai, China, in November 2011. The 262 regular session papers presented were carefully reviewed and selected from numerous submissions. The papers of part I are organized in topical sections on perception, emotion and development, bioinformatics, biologically inspired vision and recognition, bio-medical data analysis, brain signal processing, brain-computer interfaces, brain-like systems, brain-realistic models for learning, memory and embodied cognition, Clifford algebraic neural networks, combining multiple learners, computational advances in bioinformatics, and computational-intelligent human computer interaction. The second volume is structured in topical sections on cybersecurity and data mining workshop, data mining and knowledge doscovery, evolutionary design and optimisation, graphical models, human-originated data analysis and implementation, information retrieval, integrating multiple nature-inspired approaches, Kernel methods and support vector machines, and learning and memory. The third volume contains all the contributions connected with multi-agent systems, natural language processing and intelligent Web information processing, neural encoding and decoding, neural network models, neuromorphic hardware and implementations, object recognition, visual perception modelling, and advances in computational intelligence methods based pattern recognition.

Author : Janusz Kacprzyk,Witold Pedrycz
Publisher : Springer
Page : 1634 pages
File Size : 52,5 Mb
Release : 2015-05-28
Category : Technology & Engineering
ISBN : 9783662435052

Get Book

Springer Handbook of Computational Intelligence by Janusz Kacprzyk,Witold Pedrycz Pdf

The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.

Author : Martin Pelikan,Kumara Sastry,Erick Cantú-Paz
Publisher : Springer Science & Business Media
Page : 363 pages
File Size : 40,7 Mb
Release : 2006-09-25
Category : Mathematics
ISBN : 9783540349532

Get Book

Scalable Optimization via Probabilistic Modeling by Martin Pelikan,Kumara Sastry,Erick Cantú-Paz Pdf

I’m not usually a fan of edited volumes. Too often they are an incoherent hodgepodge of remnants, renegades, or rejects foisted upon an unsuspecting reading public under a misleading or fraudulent title. The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited volumes fail. For example, take the title, Scalable Optimization via Probabilistic M- eling: From Algorithms to Applications. You need not worry that you’re going to pick up this book and ?nd stray articles about anything else. This book focuseslikealaserbeamononeofthehottesttopicsinevolutionary compu- tion over the last decade or so: estimation of distribution algorithms (EDAs). EDAs borrow evolutionary computation’s population orientation and sel- tionism and throw out the genetics to give us a hybrid of substantial power, elegance, and extensibility. The article sequencing in most edited volumes is hard to understand, but from the get go the editors of this volume have assembled a set of articles sequenced in a logical fashion. The book moves from design to e?ciency enhancement and then concludes with relevant applications. The emphasis on e?ciency enhancement is particularly important, because the data-mining perspectiveimplicitinEDAsopensuptheworldofoptimizationtonewme- ods of data-guided adaptation that can further speed solutions through the construction and utilization of e?ective surrogates, hybrids, and parallel and temporal decompositions.

Author : Assad Abbas,Samee U. Khan,Albert Y. Zomaya
Publisher : John Wiley & Sons
Page : 616 pages
File Size : 55,9 Mb
Release : 2020-04-21
Category : Technology & Engineering
ISBN : 9781119551690

Get Book

Fog Computing by Assad Abbas,Samee U. Khan,Albert Y. Zomaya Pdf

Summarizes the current state and upcoming trends within the area of fog computing Written by some of the leading experts in the field, Fog Computing: Theory and Practice focuses on the technological aspects of employing fog computing in various application domains, such as smart healthcare, industrial process control and improvement, smart cities, and virtual learning environments. In addition, the Machine-to-Machine (M2M) communication methods for fog computing environments are covered in depth. Presented in two parts—Fog Computing Systems and Architectures, and Fog Computing Techniques and Application—this book covers such important topics as energy efficiency and Quality of Service (QoS) issues, reliability and fault tolerance, load balancing, and scheduling in fog computing systems. It also devotes special attention to emerging trends and the industry needs associated with utilizing the mobile edge computing, Internet of Things (IoT), resource and pricing estimation, and virtualization in the fog environments. Includes chapters on deep learning, mobile edge computing, smart grid, and intelligent transportation systems beyond the theoretical and foundational concepts Explores real-time traffic surveillance from video streams and interoperability of fog computing architectures Presents the latest research on data quality in the IoT, privacy, security, and trust issues in fog computing Fog Computing: Theory and Practice provides a platform for researchers, practitioners, and graduate students from computer science, computer engineering, and various other disciplines to gain a deep understanding of fog computing.

Author : Patricia Melin,Oscar Castillo,Janusz Kacprzyk
Publisher : Springer
Page : 838 pages
File Size : 41,8 Mb
Release : 2016-12-08
Category : Technology & Engineering
ISBN : 9783319470542

Get Book

Nature-Inspired Design of Hybrid Intelligent Systems by Patricia Melin,Oscar Castillo,Janusz Kacprzyk Pdf

This book highlights recent advances in the design of hybrid intelligent systems based on nature-inspired optimization and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction, and optimization of complex problems. The book is divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.

Author : Jan Staunton
Publisher : Unknown
Page : 0 pages
File Size : 42,6 Mb
Release : 2012
Category : Electronic
ISBN : OCLC:931187114

Get Book

Using Estimation of Distribution Algorithms to Detect Concurrent Faults by Jan Staunton Pdf

Author : Thomas Bäck,Mike Preuss,André Deutz,Hao Wang,Carola Doerr,Michael Emmerich,Heike Trautmann
Publisher : Springer Nature
Page : 753 pages
File Size : 48,9 Mb
Release : 2020-09-02
Category : Computers
ISBN : 9783030581121

Get Book

Parallel Problem Solving from Nature – PPSN XVI by Thomas Bäck,Mike Preuss,André Deutz,Hao Wang,Carola Doerr,Michael Emmerich,Heike Trautmann Pdf

This two-volume set LNCS 12269 and LNCS 12270 constitutes the refereed proceedings of the 16th International Conference on Parallel Problem Solving from Nature, PPSN 2020, held in Leiden, The Netherlands, in September 2020. The 99 revised full papers were carefully reviewed and selected from 268 submissions. The topics cover classical subjects such as automated algorithm selection and configuration; Bayesian- and surrogate-assisted optimization; benchmarking and performance measures; combinatorial optimization; connection between nature-inspired optimization and artificial intelligence; genetic and evolutionary algorithms; genetic programming; landscape analysis; multiobjective optimization; real-world applications; reinforcement learning; and theoretical aspects of nature-inspired optimization.

Author : Fabio Caraffini,Valentino Santucci,Alfredo Milani
Publisher : MDPI
Page : 286 pages
File Size : 49,5 Mb
Release : 2020-11-25
Category : Technology & Engineering
ISBN : 9783039434541

Get Book

Evolutionary Computation & Swarm Intelligence by Fabio Caraffini,Valentino Santucci,Alfredo Milani Pdf

The vast majority of real-world problems can be expressed as an optimisation task by formulating an objective function, also known as cost or fitness function. The most logical methods to optimise such a function when (1) an analytical expression is not available, (2) mathematical hypotheses do not hold, and (3) the dimensionality of the problem or stringent real-time requirements make it infeasible to find an exact solution mathematically are from the field of Evolutionary Computation (EC) and Swarm Intelligence (SI). The latter are broad and still growing subjects in Computer Science in the study of metaheuristic approaches, i.e., those approaches which do not make any assumptions about the problem function, inspired from natural phenomena such as, in the first place, the evolution process and the collaborative behaviours of groups of animals and communities, respectively. This book contains recent advances in the EC and SI fields, covering most themes currently receiving a great deal of attention such as benchmarking and tunning of optimisation algorithms, their algorithm design process, and their application to solve challenging real-world problems to face large-scale domains.

Author : Anne Auger,Benjamin Doerr
Publisher : World Scientific
Page : 370 pages
File Size : 47,7 Mb
Release : 2011
Category : Computers
ISBN : 9789814282666

Get Book

Theory of Randomized Search Heuristics by Anne Auger,Benjamin Doerr Pdf

This volume covers both classical results and the most recent theoretical developments in the field of randomized search heuristics such as runtime analysis, drift analysis and convergence.

Author : Aimin Zhou
Publisher : Unknown
Page : 0 pages
File Size : 49,7 Mb
Release : 2009
Category : Electronic
ISBN : OCLC:425819983

Get Book

Estimation of Distribution Algorithms for Continuous Multiobjective Optimization by Aimin Zhou Pdf

Author : De-Shuang Huang,Kang-Hyun Jo,Jianqiang Li,Valeriya Gribova,Vitoantonio Bevilacqua
Publisher : Springer Nature
Page : 913 pages
File Size : 54,9 Mb
Release : 2021-08-09
Category : Computers
ISBN : 9783030845223

Get Book

Intelligent Computing Theories and Application by De-Shuang Huang,Kang-Hyun Jo,Jianqiang Li,Valeriya Gribova,Vitoantonio Bevilacqua Pdf

This two-volume set of LNCS 12836 and LNCS 12837 constitutes - in conjunction with the volume LNAI 12838 - the refereed proceedings of the 17th International Conference on Intelligent Computing, ICIC 2021, held in Shenzhen, China in August 2021. The 192 full papers of the three proceedings volumes were carefully reviewed and selected from 458 submissions. The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.” The papers are organized in the following subsections: Evolutionary Computation and Learning, Image and signal Processing, Information Security, Neural Networks, Pattern Recognition Swarm Intelligence and Optimization, and Virtual Reality and Human-Computer Interaction.

Author : Agoston E. Eiben,J.E. Smith
Publisher : Springer Science & Business Media
Page : 307 pages
File Size : 48,9 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9783662050941

Get Book

Introduction to Evolutionary Computing by Agoston E. Eiben,J.E. Smith Pdf

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.