Evolutionary computation for modeling and optimization / Daniel Ashlock
Tipo de material:
TextoDetalles de publicación: New York : Springer, 2006Descripción: xix, 571 p. : il., gráficas. ; 25 cmISBN: - 0387221964 (hd.bd.)
- QA76.618 A8269
| Tipo de ítem | Biblioteca actual | Biblioteca de origen | Colección | Signatura topográfica | Copia número | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems | |
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Biblioteca Antonio Enriquez Savignac | Biblioteca Antonio Enriquez Savignac | COLECCIÓN RESERVA | QA76.618 A8269 2006 (Navegar estantería(Abre debajo)) | 1 | No para préstamo | 018283 |
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| QA76.6 T1641or 2000 Organización de computadoras : un enfoque estructurado / | QA76.6 V55 Fundamentos de programación: Aprendizaje activo basado en casos: Un Enfoque moderno usando java, UML, objetos y eclipse / | QA76.6 V55 Fundamentos de programación: Aprendizaje activo basado en casos: Un Enfoque moderno usando java, UML, objetos y eclipse / | QA76.618 A8269 2006 Evolutionary computation for modeling and optimization / | QA 76 .618 E341 Introduction to evolutionary computing / | QA 76 .62 T497 1999 Haskell : the craft of functional programming / | QA 76 .625 D43 2000 Internet and World Wide Web : how to program / |
Incluye referencias bibliográficas p. [555]-558 e índice
An Overview of Evolutionary Computation -- Designing Simple Evolutionary Algorithms -- Optimizing Real Valued Functions -- Sunburn: Co-evolving Strings -- Small Neural Nets: Symbots -- Evolving Finite State Automata -- Ordered Structures -- Plus One Recall Store -- Fitting to Data -- Tartarus: Discrete Robotics -- Evolving Logic functions -- ISAc list: Alternative Genetic Programming -- Graph Based Evolutionary Algorithms -- Cellular Encoding -- Application to Bioinformatics -- Glossary -- Appendices -- References -- Index
"Evolutionary Computation for Optimization and Modeling is an introduction to evolutionary computation, a field which includes genetic algorithms, evolutionary programming, evolution strategies, and genetic programming. The text is a survey of some application of evolutionary algorithms. It introduces mutation, crossover, design issues of selection and replacement methods, the issue of populations size, and the question of design of the fitness function. It also includes a methodological material on efficient implementation. Some of the other topics in this book include the design of simple evolutionary algorithms, applications to several types of optimization, evolutionary robotics, simple evolutionary neural computation, and several types of automatic programming including genetic programming. The book gives applications to biology and bioinformatics and introduces a number of tools that can be used in biological modeling, including evolutionary game theory. Advanced techniques such as cellular encoding, grammar based encoding, and graph based evolutionary algorithms are also covered. This book presents a large number of homework problems, projects, and experiments, with a goal of illustrating single aspects of evolutionary computation and comparing different methods. Its readership is intended for an undergraduate or first-year graduate course in evolutionary computation for computer science, engineering, or other computational science students. Engineering, computer science, and applied math students will find this book a useful guide to using evolutionary algorithms as a problem solving too"--P. web LC
Compra 090319 0
