Gecco 99
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Author |
: |
Publisher |
: Morgan Kaufmann |
Total Pages |
: 948 |
Release |
: 1999 |
ISBN-10 |
: STANFORD:36105021832063 |
ISBN-13 |
: |
Rating |
: 4/5 (63 Downloads) |
Synopsis GECCO-99 by :
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 |
: Wolfgang Banzhaf |
Publisher |
: |
Total Pages |
: 968 |
Release |
: 1999 |
ISBN-10 |
: UCSD:31822028566669 |
ISBN-13 |
: |
Rating |
: 4/5 (69 Downloads) |
Synopsis GECCO-99 by : Wolfgang Banzhaf
Author |
: Alex A. Freitas |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 272 |
Release |
: 2013-11-11 |
ISBN-10 |
: 9783662049235 |
ISBN-13 |
: 3662049236 |
Rating |
: 4/5 (35 Downloads) |
Synopsis Data Mining and Knowledge Discovery with Evolutionary Algorithms by : Alex A. Freitas
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 |
: Riccardo Poli |
Publisher |
: Springer |
Total Pages |
: 371 |
Release |
: 2004-05-24 |
ISBN-10 |
: 9783540462392 |
ISBN-13 |
: 3540462392 |
Rating |
: 4/5 (92 Downloads) |
Synopsis Genetic Programming by : Riccardo Poli
This volume contains the proceedings of EuroGP 2000, the European Conf- ence on Genetic Programming, held in Edinburgh on the 15th and 16th April 2000. This event was the third in a series which started with the two European workshops: EuroGP’98, held in Paris in April 1998, and EuroGP’99, held in Gothenburg in May 1999. EuroGP 2000 was held in conjunction with EvoWo- shops 2000 (17th April) and ICES 2000 (17th-19th April). Genetic Programming (GP) is a growing branch of Evolutionary Compu- tion in which the structures in the population being evolved are computer p- grams. GP has been applied successfully to a large number of di?cult problems like automatic design, pattern recognition, robotic control, synthesis of neural networks, symbolic regression, music and picture generation, biomedical app- cations, etc. In recent years,even human-competitive results have been achieved by a number of groups. EuroGP 2000, the ?rst evolutionary computation conference of the new m- lennium, was the biggest event devoted to genetic programming to be held in Europe in 2000. It was a high quality conference where state-of-the-art work on the theory of GP and applications of GP to real world problems was presented.
Author |
: Martin V. Butz |
Publisher |
: Springer |
Total Pages |
: 279 |
Release |
: 2006-01-04 |
ISBN-10 |
: 9783540312314 |
ISBN-13 |
: 3540312315 |
Rating |
: 4/5 (14 Downloads) |
Synopsis Rule-Based Evolutionary Online Learning Systems by : Martin V. Butz
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 |
: F.J. Lobo |
Publisher |
: Springer |
Total Pages |
: 323 |
Release |
: 2007-04-03 |
ISBN-10 |
: 9783540694328 |
ISBN-13 |
: 3540694323 |
Rating |
: 4/5 (28 Downloads) |
Synopsis Parameter Setting in Evolutionary Algorithms by : F.J. Lobo
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 |
: Rick Riolo |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 322 |
Release |
: 2012-12-06 |
ISBN-10 |
: 9781441989833 |
ISBN-13 |
: 1441989838 |
Rating |
: 4/5 (33 Downloads) |
Synopsis Genetic Programming Theory and Practice by : Rick Riolo
Genetic Programming Theory and Practice explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). The material contained in this contributed volume was developed from a workshop at the University of Michigan's Center for the Study of Complex Systems where an international group of genetic programming theorists and practitioners met to examine how GP theory informs practice and how GP practice impacts GP theory. The contributions cover the full spectrum of this relationship and are written by leading GP theorists from major universities, as well as active practitioners from leading industries and businesses. Chapters include such topics as John Koza's development of human-competitive electronic circuit designs; David Goldberg's application of "competent GA" methodology to GP; Jason Daida's discovery of a new set of factors underlying the dynamics of GP starting from applied research; and Stephen Freeland's essay on the lessons of biology for GP and the potential impact of GP on evolutionary theory.
Author |
: Rennard, Jean-Philippe |
Publisher |
: IGI Global |
Total Pages |
: 1066 |
Release |
: 2006-09-30 |
ISBN-10 |
: 9781591409854 |
ISBN-13 |
: 1591409853 |
Rating |
: 4/5 (54 Downloads) |
Synopsis Handbook of Research on Nature-Inspired Computing for Economics and Management by : Rennard, Jean-Philippe
"This book provides applications of nature inspired computing for economic theory and practice, finance and stock-market, manufacturing systems, marketing, e-commerce, e-auctions, multi-agent systems and bottom-up simulations for social sciences and operations management"--Provided by publisher.
Author |
: K. C. Tan |
Publisher |
: World Scientific |
Total Pages |
: 836 |
Release |
: 2004 |
ISBN-10 |
: 9789812389527 |
ISBN-13 |
: 9812389520 |
Rating |
: 4/5 (27 Downloads) |
Synopsis Recent Advances in Simulated Evolution and Learning by : K. C. Tan
This book covers the latest advances in the theories, algorithms, and applications of simulated evolution and learning techniques. It provides insights into different evolutionary computation techniques and their applications in domains such as scheduling, control and power, robotics, signal processing, and bioinformatics. The book will be of significant value to all postgraduates, research scientists and practitioners dealing with evolutionary computation or complex real-world problems.
Author |
: Mitra Basu |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 309 |
Release |
: 2006-12-22 |
ISBN-10 |
: 9781846281723 |
ISBN-13 |
: 1846281725 |
Rating |
: 4/5 (23 Downloads) |
Synopsis Data Complexity in Pattern Recognition by : Mitra Basu
Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.