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Proceedings of the 2000 Congress on Evolutionary Computation

Proceedings of the 2000 Congress on Evolutionary Computation PDF Author:
Publisher:
ISBN:
Category : Evolutionary computation
Languages : en
Pages : 802

Book Description


Proceedings of the 2000 Congress on Evolutionary Computation

Proceedings of the 2000 Congress on Evolutionary Computation PDF Author:
Publisher:
ISBN:
Category : Evolutionary computation
Languages : en
Pages : 802

Book Description


Proceedings of the ... Congress on Evolutionary Computation

Proceedings of the ... Congress on Evolutionary Computation PDF Author:
Publisher:
ISBN:
Category : Evolutionary computation
Languages : en
Pages : 1258

Book Description


Introduction to Evolutionary Computing

Introduction to Evolutionary Computing PDF Author: A.E. Eiben
Publisher: Springer Science & Business Media
ISBN: 9783540401841
Category : Computers
Languages : en
Pages : 328

Book Description
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.

Evolutionary Computation in Dynamic and Uncertain Environments

Evolutionary Computation in Dynamic and Uncertain Environments PDF Author: Shengxiang Yang
Publisher: Springer
ISBN: 3540497749
Category : Technology & Engineering
Languages : en
Pages : 614

Book Description
This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.

Evolutionary Multi-Criterion Optimization

Evolutionary Multi-Criterion Optimization PDF Author: Carlos A. Coello Coello
Publisher: Springer Science & Business Media
ISBN: 3540249834
Category : Computers
Languages : en
Pages : 927

Book Description
This book constitutes the refereed proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization, EMO 2005, held in Guanajuato, Mexico, in March 2005. The 59 revised full papers presented together with 2 invited papers and the summary of a tutorial were carefully reviewed and selected from the 115 papers submitted. The papers are organized in topical sections on algorithm improvements, incorporation of preferences, performance analysis and comparison, uncertainty and noise, alternative methods, and applications in a broad variety of fields.

Computational Intelligence: A Compendium

Computational Intelligence: A Compendium PDF Author: John Fulcher
Publisher: Springer
ISBN: 3540782931
Category : Technology & Engineering
Languages : en
Pages : 1182

Book Description
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.

Evolutionary Algorithms for Solving Multi-Objective Problems

Evolutionary Algorithms for Solving Multi-Objective Problems PDF Author: Carlos Coello Coello
Publisher: Springer Science & Business Media
ISBN: 1475751842
Category : Computers
Languages : en
Pages : 600

Book Description
Researchers and practitioners alike are increasingly turning to search, op timization, and machine-learning procedures based on natural selection and natural genetics to solve problems across the spectrum of human endeavor. These genetic algorithms and techniques of evolutionary computation are solv ing problems and inventing new hardware and software that rival human designs. The Kluwer Series on Genetic Algorithms and Evolutionary Computation pub lishes research monographs, edited collections, and graduate-level texts in this rapidly growing field. Primary areas of coverage include the theory, implemen tation, and application of genetic algorithms (GAs), evolution strategies (ESs), evolutionary programming (EP), learning classifier systems (LCSs) and other variants of genetic and evolutionary computation (GEC). The series also pub lishes texts in related fields such as artificial life, adaptive behavior, artificial immune systems, agent-based systems, neural computing, fuzzy systems, and quantum computing as long as GEC techniques are part of or inspiration for the system being described. This encyclopedic volume on the use of the algorithms of genetic and evolu tionary computation for the solution of multi-objective problems is a landmark addition to the literature that comes just in the nick of time. Multi-objective evolutionary algorithms (MOEAs) are receiving increasing and unprecedented attention. Researchers and practitioners are finding an irresistible match be tween the popUlation available in most genetic and evolutionary algorithms and the need in multi-objective problems to approximate the Pareto trade-off curve or surface.

Data Mining and Knowledge Discovery with Evolutionary Algorithms

Data Mining and Knowledge Discovery with Evolutionary Algorithms PDF Author: Alex A. Freitas
Publisher: Springer Science & Business Media
ISBN: 3662049236
Category : Computers
Languages : en
Pages : 272

Book Description
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

Advances in Computation and Intelligence

Advances in Computation and Intelligence PDF Author: Zhenhua Li
Publisher: Springer
ISBN: 3642048439
Category : Computers
Languages : en
Pages : 566

Book Description
Volumes CCIS 51 and LNCS 5812 constitute the proceedings of the Fourth Interational Symposium on Intelligence Computation and Applications, ISICA 2009, held in Huangshi, China, during October 23-25. ISICA 2009 attracted over 300 submissions. Through rigorous reviews, 58 papers were included in LNCS 5821, and 54 papers were collected in CCIS 51. ISICA conferences are one of the first series of international conferences on computational intelligence that combine elements of learning, adaptation, evolution and fuzzy logic to create programs as alternative solutions to artificial intelligence.

Knowledge Incorporation in Evolutionary Computation

Knowledge Incorporation in Evolutionary Computation PDF Author: Yaochu Jin
Publisher: Springer
ISBN: 3540445110
Category : Mathematics
Languages : en
Pages : 543

Book Description
Incorporation of a priori knowledge, such as expert knowledge, meta-heuristics and human preferences, as well as domain knowledge acquired during evolu tionary search, into evolutionary algorithms has received increasing interest in the recent years. It has been shown from various motivations that knowl edge incorporation into evolutionary search is able to significantly improve search efficiency. However, results on knowledge incorporation in evolution ary computation have been scattered in a wide range of research areas and a systematic handling of this important topic in evolutionary computation still lacks. This edited book is a first attempt to put together the state-of-art and re cent advances on knowledge incorporation in evolutionary computation within a unified framework. Existing methods for knowledge incorporation are di vided into the following five categories according to the functionality of the incorporated knowledge in the evolutionary algorithms. 1. Knowledge incorporation in representation, population initialization, - combination and mutation. 2. Knowledge incorporation in selection and reproduction. 3. Knowledge incorporation in fitness evaluations. 4. Knowledge incorporation through life-time learning and human-computer interactions. 5. Incorporation of human preferences in multi-objective evolutionary com putation. The intended readers of this book are graduate students, researchers and practitioners in all fields of science and engineering who are interested in evolutionary computation. The book is divided into six parts. Part I contains one introductory chapter titled "A selected introduction to evolutionary computation" by Yao, which presents a concise but insightful introduction to evolutionary computation.