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Recent advances in simulated evolution and learning /
Inspired by the Darwinian framework of evolution through natural selection and adaptation, the field of evolutionary computation has been growing very rapidly, and is today involved in many diverse application areas. This book covers the latest advances in the theories, algorithms, and applications...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Singapore ; River Edge, NJ :
World Scientific,
©2004.
|
| Colección: | Advances in natural computation ;
v. 2. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Recent advances in simulated evolution and learning / |c editors, Kay Chen Tan [and others]. |
| 260 | |a Singapore ; |a River Edge, NJ : |b World Scientific, |c ©2004. | ||
| 300 | |a 1 online resource (xii, 820 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a Advances in natural computation ; |v v. 2 | |
| 500 | |a "This volume contains substantially extended and revised papers selected from the 4th Asia-Pacific Conference on Simulated Evolution and Learning (SEAL'2002), 18-22 November 2002, Singapore."--Preface | ||
| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Print version record. | |
| 520 | |a Inspired by the Darwinian framework of evolution through natural selection and adaptation, the field of evolutionary computation has been growing very rapidly, and is today involved in many diverse application areas. 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. | ||
| 505 | 0 | |a Preface ; PART 1: Evolutionary Theory ; Chapter 1: Co-Evolutionary Learning in Strategic Environments ; Chapter 2: Using Evolution to Learn User Preferences ; Chapter 3: A Parallel Genetic Algorithm for Clustering. | |
| 505 | 8 | |a Chapter 4: Using SIMD Genetic Programming for Fault-Tolerant Trading Strategies Chapter 5: An Efficient Coevolutionary Algorithm Based on Merging and Splitting of Species ; Chapter 6: Schema Analysis of Genetic Algorithms on Multiplicative Landscape. | |
| 505 | 8 | |a Chapter 7: Evolutionary Learning Strategies for Artificial Life Characters Chapter 8: Adaptive Strategy for GA Inspired by Biological Evolution ; Chapter 9: The Influence of Stochastic Quality Functions on Evolutionary Search. | |
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Computer simulation |v Congresses. | |
| 650 | 0 | |a Evolutionary programming (Computer science) |v Congresses. | |
| 650 | 6 | |a Simulation par ordinateur |v Congrès. | |
| 650 | 6 | |a Programmation évolutive |v Congrès. | |
| 650 | 7 | |a COMPUTERS |x Computer Simulation. |2 bisacsh | |
| 650 | 7 | |a Computer simulation |2 fast | |
| 650 | 7 | |a Evolutionary programming (Computer science) |2 fast | |
| 655 | 7 | |a Conference papers and proceedings |2 fast | |
| 700 | 1 | |a Tan, K. C. | |
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| 830 | 0 | |a Advances in natural computation ; |v v. 2. | |
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