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Genetic Algorithms—Principles and Perspectives [electronic resource] : A Guide to GA Theory /
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and t...
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| Format: | Texto biblioteca |
| Language: | eng |
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Boston, MA : Springer US,
2002
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| Subjects: | Computer science., Operations research., Decision making., Artificial intelligence., Mathematical optimization., Statistics., Computer Science., Artificial Intelligence (incl. Robotics)., Optimization., Statistics, general., Operation Research/Decision Theory., |
| Online Access: | http://dx.doi.org/10.1007/b101880 |
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KOHA-OAI-TEST:1702912018-07-30T22:47:01ZGenetic Algorithms—Principles and Perspectives [electronic resource] : A Guide to GA Theory / Reeves, Colin R. author. Rowe, Jonathan E. author. SpringerLink (Online service) textBoston, MA : Springer US,2002.engGenetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch", GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems.Basic Principles -- Schema Theory -- No Free Lunch for GAs -- GAs as Markov Processes -- The Dynamical Systems Model -- Statistical Mechanics Approximations -- Predicting GA Performance -- Landscapes -- Summary.Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch", GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems.Computer science.Operations research.Decision making.Artificial intelligence.Mathematical optimization.Statistics.Computer Science.Artificial Intelligence (incl. Robotics).Optimization.Statistics, general.Operation Research/Decision Theory.Springer eBookshttp://dx.doi.org/10.1007/b101880URN:ISBN:9780306480508 |
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Departamento de documentación y biblioteca de COLPOS |
| language |
eng |
| topic |
Computer science. Operations research. Decision making. Artificial intelligence. Mathematical optimization. Statistics. Computer Science. Artificial Intelligence (incl. Robotics). Optimization. Statistics, general. Operation Research/Decision Theory. Computer science. Operations research. Decision making. Artificial intelligence. Mathematical optimization. Statistics. Computer Science. Artificial Intelligence (incl. Robotics). Optimization. Statistics, general. Operation Research/Decision Theory. |
| spellingShingle |
Computer science. Operations research. Decision making. Artificial intelligence. Mathematical optimization. Statistics. Computer Science. Artificial Intelligence (incl. Robotics). Optimization. Statistics, general. Operation Research/Decision Theory. Computer science. Operations research. Decision making. Artificial intelligence. Mathematical optimization. Statistics. Computer Science. Artificial Intelligence (incl. Robotics). Optimization. Statistics, general. Operation Research/Decision Theory. Reeves, Colin R. author. Rowe, Jonathan E. author. SpringerLink (Online service) Genetic Algorithms—Principles and Perspectives [electronic resource] : A Guide to GA Theory / |
| description |
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch", GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems. |
| format |
Texto |
| topic_facet |
Computer science. Operations research. Decision making. Artificial intelligence. Mathematical optimization. Statistics. Computer Science. Artificial Intelligence (incl. Robotics). Optimization. Statistics, general. Operation Research/Decision Theory. |
| author |
Reeves, Colin R. author. Rowe, Jonathan E. author. SpringerLink (Online service) |
| author_facet |
Reeves, Colin R. author. Rowe, Jonathan E. author. SpringerLink (Online service) |
| author_sort |
Reeves, Colin R. author. |
| title |
Genetic Algorithms—Principles and Perspectives [electronic resource] : A Guide to GA Theory / |
| title_short |
Genetic Algorithms—Principles and Perspectives [electronic resource] : A Guide to GA Theory / |
| title_full |
Genetic Algorithms—Principles and Perspectives [electronic resource] : A Guide to GA Theory / |
| title_fullStr |
Genetic Algorithms—Principles and Perspectives [electronic resource] : A Guide to GA Theory / |
| title_full_unstemmed |
Genetic Algorithms—Principles and Perspectives [electronic resource] : A Guide to GA Theory / |
| title_sort |
genetic algorithms—principles and perspectives [electronic resource] : a guide to ga theory / |
| publisher |
Boston, MA : Springer US, |
| publishDate |
2002 |
| url |
http://dx.doi.org/10.1007/b101880 |
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