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Author : Wolfgang Banzhaf
Publisher :
ISBN 13 :
Total Pages : 968 pages
Book Rating : 4.:/5 (318 download)
Download or read book GECCO-99 written by Wolfgang Banzhaf and published by . This book was released on 1999 with total page 968 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher : Morgan Kaufmann
ISBN 13 :
Total Pages : 948 pages
Book Rating : 4.F/5 ( download)
Download or read book GECCO-99 written by and published by Morgan Kaufmann. This book was released on 1999 with total page 948 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings contain the papers presented at the GECCO conference, held in Orlando, Florida, July 13-17, 1999. The 1999 Genetic and Evolutionary Computational Conference (GECCO-99) combined the longest running conferences in evolutionary computation (ICGA) and the world's two largest EC conferences (GP and ICGA) to create a unique opportunity to collect the best in research in this growing field of computer science and engineering.
Author : Pier L. Lanzi
Publisher : Springer
ISBN 13 : 3540446400
Total Pages : 270 pages
Book Rating : 4.5/5 (44 download)
Download or read book Advances in Learning Classifier Systems written by Pier L. Lanzi and published by Springer. This book was released on 2003-07-31 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning classi er systems are rule-based systems that exploit evolutionary c- putation and reinforcement learning to solve di cult problems. They were - troduced in 1978 by John H. Holland, the father of genetic algorithms, and since then they have been applied to domains as diverse as autonomous robotics, trading agents, and data mining. At the Second International Workshop on Learning Classi er Systems (IWLCS 99), held July 13, 1999, in Orlando, Florida, active researchers reported on the then current state of learning classi er system research and highlighted some of the most promising research directions. The most interesting contri- tions to the meeting are included in the book Learning Classi er Systems: From Foundations to Applications, published as LNAI 1813 by Springer-Verlag. The following year, the Third International Workshop on Learning Classi er Systems (IWLCS 2000), held September 15{16 in Paris, gave participants the opportunity to discuss further advances in learning classi er systems. We have included in this volume revised and extended versions of thirteen of the papers presented at the workshop.
Author : Alex A. Freitas
Publisher : Springer Science & Business Media
ISBN 13 : 3662049236
Total Pages : 272 pages
Book Rating : 4.6/5 (62 download)
Download or read book Data Mining and Knowledge Discovery with Evolutionary Algorithms written by Alex A. Freitas and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics
Author : Darpa
Publisher : Morgan Kaufmann
ISBN 13 : 9781558606388
Total Pages : 302 pages
Book Rating : 4.6/5 (63 download)
Download or read book Broadcast News Workshop '99 Proceedings written by Darpa and published by Morgan Kaufmann. This book was released on 1999-06-29 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jan Pavelka
Publisher : Springer
ISBN 13 : 3540478493
Total Pages : 510 pages
Book Rating : 4.5/5 (44 download)
Download or read book SOFSEM'99: Theory and Practice of Informatics written by Jan Pavelka and published by Springer. This book was released on 2003-07-31 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: This year the SOFSEM conference is coming back to Milovy in Moravia to th be held for the 26 time. Although born as a local Czechoslovak event 25 years ago SOFSEM did not miss the opportunity oe red in 1989 by the newly found freedom in our part of Europe and has evolved into a full-?edged international conference. For all the changes, however, it has kept its generalist and mul- disciplinarycharacter.Thetracksofinvitedtalks,rangingfromTrendsinTheory to Software and Information Engineering, attest to this. Apart from the topics mentioned above, SOFSEM’99 oer s invited talks exploring core technologies, talks tracing the path from data to knowledge, and those describing a wide variety of applications. TherichcollectionofinvitedtalkspresentsonetraditionalfacetofSOFSEM: that of a winter school, in which IT researchers and professionals get an opp- tunity to see more of the large pasture of today’s computing than just their favourite grazing corner. To facilitate this purpose the prominent researchers delivering invited talks usually start with a broad overview of the state of the art in a wider area and then gradually focus on their particular subject.
Author : Ying-ping Chen
Publisher : Springer Science & Business Media
ISBN 13 : 9783540284598
Total Pages : 152 pages
Book Rating : 4.2/5 (845 download)
Download or read book Extending the Scalability of Linkage Learning Genetic Algorithms written by Ying-ping Chen and published by Springer Science & Business Media. This book was released on 2006 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms (GAs) are powerful search techniques based on principles of evolution and widely applied to solve problems in many disciplines. However, most GAs employed in practice nowadays are unable to learn genetic linkage and suffer from the linkage problem. The linkage learning genetic algorithm (LLGA) was proposed to tackle the linkage problem with several specially designed mechanisms. While the LLGA performs much better on badly scaled problems than simple GAs, it does not work well on uniformly scaled problems as other competent GAs. Therefore, we need to understand why it is so and need to know how to design a better LLGA or whether there are certain limits of such a linkage learning process. This book aims to gain better understanding of the LLGA in theory and to improve the LLGA's performance in practice. It starts with a survey of the existing genetic linkage learning techniques and describes the steps and approaches taken to tackle the research topics, including using promoters, developing the convergence time model, and adopting subchromosomes.
Author : John S. Gero
Publisher : Springer Science & Business Media
ISBN 13 : 9401141541
Total Pages : 700 pages
Book Rating : 4.4/5 (11 download)
Download or read book Artificial Intelligence in Design ’00 written by John S. Gero and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing is one of the foundations for change in our society. It is a fundamental precursor to manufacturing, fabrication and construction. Design research aims to develop an understanding of designing and to produce models of designing that can be used to aid designing. The papers in this volume are from the Sixth International Conference on Artificial Intelligence in Design (AID'00) held in June 2000, in Worcester, Massachusetts, USA. They represent the state of the art and the cutting edge of research and development in this field, and demonstrate both the depth and breadth of the artificial intelligence paradigm in design. They point the way for the development of advanced computer-based tools to aid designers, and describe advances in both theory and application. This volume will be of particular interest to researchers, developers, and users of advanced computer systems in design.
Author : Martin V. Butz
Publisher : Springer
ISBN 13 : 3540312315
Total Pages : 279 pages
Book Rating : 4.5/5 (43 download)
Download or read book Rule-Based Evolutionary Online Learning Systems written by Martin V. Butz and published by Springer. This book was released on 2006-01-04 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rule-basedevolutionaryonlinelearningsystems,oftenreferredtoasMichig- style learning classi?er systems (LCSs), were proposed nearly thirty years ago (Holland, 1976; Holland, 1977) originally calling them cognitive systems. LCSs combine the strength of reinforcement learning with the generali- tion capabilities of genetic algorithms promising a ?exible, online general- ing, solely reinforcement dependent learning system. However, despite several initial successful applications of LCSs and their interesting relations with a- mal learning and cognition, understanding of the systems remained somewhat obscured. Questions concerning learning complexity or convergence remained unanswered. Performance in di?erent problem types, problem structures, c- ceptspaces,andhypothesisspacesstayednearlyunpredictable. Thisbookhas the following three major objectives: (1) to establish a facetwise theory - proachforLCSsthatpromotessystemanalysis,understanding,anddesign;(2) to analyze, evaluate, and enhance the XCS classi?er system (Wilson, 1995) by the means of the facetwise approach establishing a fundamental XCS learning theory; (3) to identify both the major advantages of an LCS-based learning approach as well as the most promising potential application areas. Achieving these three objectives leads to a rigorous understanding of LCS functioning that enables the successful application of LCSs to diverse problem types and problem domains. The quantitative analysis of XCS shows that the inter- tive, evolutionary-based online learning mechanism works machine learning competitively yielding a low-order polynomial learning complexity. Moreover, the facetwise analysis approach facilitates the successful design of more - vanced LCSs including Holland’s originally envisioned cognitive systems. Martin V.
Author : Pier L. Lanzi
Publisher : Springer
ISBN 13 : 3540450270
Total Pages : 344 pages
Book Rating : 4.5/5 (44 download)
Download or read book Learning Classifier Systems written by Pier L. Lanzi and published by Springer. This book was released on 2003-06-26 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This book provides a unique survey of the current state of the art of LCS and highlights some of the most promising research directions. The first part presents various views of leading people on what learning classifier systems are. The second part is devoted to advanced topics of current interest, including alternative representations, methods for evaluating rule utility, and extensions to existing classifier system models. The final part is dedicated to promising applications in areas like data mining, medical data analysis, economic trading agents, aircraft maneuvering, and autonomous robotics. An appendix comprising 467 entries provides a comprehensive LCS bibliography.
Author : Martin Pelikan
Publisher : Springer
ISBN 13 : 3540349545
Total Pages : 363 pages
Book Rating : 4.5/5 (43 download)
Download or read book Scalable Optimization via Probabilistic Modeling written by Martin Pelikan and published by Springer. This book was released on 2007-01-12 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Una-May O'Reilly
Publisher : Springer Science & Business Media
ISBN 13 : 0387232540
Total Pages : 330 pages
Book Rating : 4.3/5 (872 download)
Download or read book Genetic Programming Theory and Practice II written by Una-May O'Reilly and published by Springer Science & Business Media. This book was released on 2006-03-16 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: The work described in this book was first presented at the Second Workshop on Genetic Programming, Theory and Practice, organized by the Center for the Study of Complex Systems at the University of Michigan, Ann Arbor, 13-15 May 2004. The goal of this workshop series is to promote the exchange of research results and ideas between those who focus on Genetic Programming (GP) theory and those who focus on the application of GP to various re- world problems. In order to facilitate these interactions, the number of talks and participants was small and the time for discussion was large. Further, participants were asked to review each other's chapters before the workshop. Those reviewer comments, as well as discussion at the workshop, are reflected in the chapters presented in this book. Additional information about the workshop, addendums to chapters, and a site for continuing discussions by participants and by others can be found at http://cscs.umich.edu:8000/GPTP-20041. We thank all the workshop participants for making the workshop an exciting and productive three days. In particular we thank all the authors, without whose hard work and creative talents, neither the workshop nor the book would be possible. We also thank our keynote speakers Lawrence ("Dave") Davis of NuTech Solutions, Inc., Jordan Pollack of Brandeis University, and Richard Lenski of Michigan State University, who delivered three thought-provoking speeches that inspired a great deal of discussion among the participants.
Author : John Fulcher
Publisher : Springer
ISBN 13 : 3540782931
Total Pages : 1182 pages
Book Rating : 4.5/5 (47 download)
Download or read book Computational Intelligence: A Compendium written by John Fulcher and published by Springer. This book was released on 2008-05-28 with total page 1182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence: A Compendium presents a well structured overview about this rapidly growing field with contributions from leading experts in Computational Intelligence. The main focus of the compendium is on applied methods, tried-and-proven as being effective to realworld problems, which is especially useful for practitioners, researchers, students and also newcomers to the field. This state-of- handbook-style book has contributions by leading experts.
Author : Thomas Philip Runarsson
Publisher : Springer Science & Business Media
ISBN 13 : 3540389903
Total Pages : 1079 pages
Book Rating : 4.5/5 (43 download)
Download or read book Parallel Problem Solving from Nature - PPSN IX written by Thomas Philip Runarsson and published by Springer Science & Business Media. This book was released on 2006-09-13 with total page 1079 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Parallel Problem Solving from Nature, PPSN 2006. The book presents 106 revised full papers covering a wide range of topics, from evolutionary computation to swarm intelligence and bio-inspired computing to real-world applications. These are organized in topical sections on theory, new algorithms, applications, multi-objective optimization, evolutionary learning, as well as representations, operators, and empirical evaluation.
Author : F.J. Lobo
Publisher : Springer
ISBN 13 : 3540694323
Total Pages : 323 pages
Book Rating : 4.5/5 (46 download)
Download or read book Parameter Setting in Evolutionary Algorithms written by F.J. Lobo and published by Springer. This book was released on 2007-04-03 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.
Author : R. Paton
Publisher : Springer Science & Business Media
ISBN 13 : 3662063697
Total Pages : 349 pages
Book Rating : 4.6/5 (62 download)
Download or read book Computation in Cells and Tissues written by R. Paton and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of biologically inspired computation has coexisted with mainstream computing since the 1930s, and the pioneers in this area include Warren McCulloch, Walter Pitts, Robert Rosen, Otto Schmitt, Alan Turing, John von Neumann and Norbert Wiener. Ideas arising out of studies of biology have permeated algorithmics, automata theory, artificial intelligence, graphics, information systems and software design. Within this context, the biomolecular, cellular and tissue levels of biological organisation have had a considerable inspirational impact on the development of computational ideas. Such innovations include neural computing, systolic arrays, genetic and immune algorithms, cellular automata, artificial tissues, DNA computing and protein memories. With the rapid growth in biological knowledge there remains a vast source of ideas yet to be tapped. This includes developments associated with biomolecular, genomic, enzymic, metabolic, signalling and developmental systems and the various impacts on distributed, adaptive, hybrid and emergent computation. This multidisciplinary book brings together a collection of chapters by biologists, computer scientists, engineers and mathematicians who were drawn together to examine the ways in which the interdisciplinary displacement of concepts and ideas could develop new insights into emerging computing paradigms. Funded by the UK Engineering and Physical Sciences Research Council (EPSRC), the CytoCom Network formally met on five occasions to examine and discuss common issues in biology and computing that could be exploited to develop emerging models of computation.
Author : Erick Cantú-Paz
Publisher : Springer Science & Business Media
ISBN 13 : 146154369X
Total Pages : 171 pages
Book Rating : 4.4/5 (615 download)
Download or read book Efficient and Accurate Parallel Genetic Algorithms written by Erick Cantú-Paz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: As genetic algorithms (GAs) become increasingly popular, they are applied to difficult problems that may require considerable computations. In such cases, parallel implementations of GAs become necessary to reach high-quality solutions in reasonable times. But, even though their mechanics are simple, parallel GAs are complex non-linear algorithms that are controlled by many parameters, which are not well understood. Efficient and Accurate Parallel Genetic Algorithms is about the design of parallel GAs. It presents theoretical developments that improve our understanding of the effect of the algorithm's parameters on its search for quality and efficiency. These developments are used to formulate guidelines on how to choose the parameter values that minimize the execution time while consistently reaching solutions of high quality. Efficient and Accurate Parallel Genetic Algorithms can be read in several ways, depending on the readers' interests and their previous knowledge about these algorithms. Newcomers to the field will find the background material in each chapter useful to become acquainted with previous work, and to understand the problems that must be faced to design efficient and reliable algorithms. Potential users of parallel GAs that may have doubts about their practicality or reliability may be more confident after reading this book and understanding the algorithms better. Those who are ready to try a parallel GA on their applications may choose to skim through the background material, and use the results directly without following the derivations in detail. These readers will find that using the results can help them to choose the type of parallel GA that best suits their needs, without having to invest the time to implement and test various options. Once that is settled, even the most experienced users dread the long and frustrating experience of configuring their algorithms by trial and error. The guidelines contained herein will shorten dramatically the time spent tweaking the algorithm, although some experimentation may still be needed for fine-tuning. Efficient and Accurate Parallel Genetic Algorithms is suitable as a secondary text for a graduate level course, and as a reference for researchers and practitioners in industry.
