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Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, Third Edition - David B. Fogel
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ISBN: 0471669512

[SR: 2942160], Hardcover, [EAN: 9780471669517], Wiley-IEEE Press, Wiley-IEEE Press, Book, [PU: Wiley-IEEE Press], Wiley-IEEE Press, This Third Edition provides the latest tools and techniques that enable computers to learn The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does. Readers gain an understanding of the history of evolutionary computation, which provides a foundation for the author's thorough presentation of the latest theories shaping current research. Balancing theory with practice, the author provides readers with the skills they need to apply evolutionary algorithms that can solve many of today's intransigent problems by adapting to new challenges and learning from experience. Several examples are provided that demonstrate how these evolutionary algorithms learn to solve problems. In particular, the author provides a detailed example of how an algorithm is used to evolve strategies for playing chess and checkers. As readers progress through the publication, they gain an increasing appreciation and understanding of the relationship between learning and intelligence. Readers familiar with the previous editions will discover much new and revised material that brings the publication thoroughly up to date with the latest research, including the latest theories and empirical properties of evolutionary computation. The Third Edition also features new knowledge-building aids. Readers will find a host of new and revised examples. New questions at the end of each chapter enable readers to test their knowledge. Intriguing assignments that prepare readers to manage challenges in industry and research have been added to the end of each chapter as well. This is a must-have reference for professionals in computer and electrical engineering; it provides them with the very latest techniques and applications in machine intelligence. With its question sets and assignments, the publication is also recommended as a graduate-level textbook., 280291, Intelligence & Semantics, 3887, AI & Machine Learning, 3508, Computer Science, 5, Computers & Technology, 1000, Subjects, 283155, Books, 4053, Software, 69760, Accounting, 6133990011, Adobe, 10806626011, Databases, 10806627011, Design & Graphics, 4164, E-mail, 10806628011, Enterprise Applications, 271582011, Mathematical & Statistical, 10806637011, Microsoft, 132553011, Optical Character Recognition, 4169, Personal Finance, 10806632011, Presentation Software, 10806633011, Project Management Software, 69761, Quickbooks, 10806634011, Spreadsheets, 10806635011, Suites, 4072, Utilities, 300354, Voice Recognition, 10806636011, Word Processing, 5, Computers & Technology, 1000, Subjects, 283155, Books, 13707, Electronics, 13718, Microelectronics, 13723, Optoelectronics, 13725, Semiconductors, 107183011, Sensors, 13727, Solid State, 227548, Transistors, 227544, Electrical & Electronics, 173515, Engineering, 173507, Engineering & Transportation, 1000, Subjects, 283155, Books, 13809, Telecommunications & Sensors, 107172011, Antennas, 13816, Microwaves, 7976022011, Mobile & Wireless, 3747, Networks, 13801, Radar, 13818, Radio, 13684, Remote Sensing & GIS, 107177011, Satellite, 7921655011, Signal Processing, 13820, Telephone Systems, 13822, Television & Video, 173515, Engineering, 173507, Engineering & Transportation, 1000, Subjects, 283155, Books, 13884, Mathematics, 226699, Applied, 226700, Geometry & Topology, 13942, History, 13944, Infinity, 13955, Mathematical Analysis, 13957, Matrices, 13961, Number Systems, 13965, Popular & Elementary, 226698, Pure Mathematics, 13979, Reference, 13981, Research, 13985, Study & Teaching, 13989, Transformations, 13991, Trigonometry, 75, Science & Math, 1000, Subjects, 283155, Books, 465600, New, Used & Rental Textbooks, 468220, Business & Finance, 468226, Communication & Journalism, 468204, Computer Science, 468224, Education, 468212, Engineering, 468206, Humanities, 468222, Law, 468228, Medicine & Health Sciences, 684283011, Reference, 468216, Science & Mathematics, 468214, Social Sciences, 684300011, Test Prep & Study Guides, 2349030011, Specialty Boutique, 283155, Books

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Evolutionary Computation: Toward a New Philosophy of Machine Intelligence - Fogel, David B.
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Evolutionary Computation: Toward a New Philosophy of Machine Intelligence - gebrauchtes Buch

ISBN: 9780471669517

ID: 1569191

This Third Edition provides the latest tools and techniques that enable computers to learn The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does. Readers gain an understanding of the history of evolutionary computation, which provides a foundation for the author's thorough presentation of the latest theories shaping current research. Balancing theory with practice, the author provides readers with the skills they need to apply evolutionary algorithms that can solve many of today's intransigent problems by adapting to new challenges and learning from experience. Several examples are provided that demonstrate how these evolutionary algorithms learn to solve problems. In particular, the author provides a detailed example of how an algorithm is used to evolve strategies for playing chess and checkers. As readers progress through the publication, they gain an increasing appreciation and understanding of the relationship between learning and intelligence. Readers familiar with the previous editions will discover much new and revised material that brings the publication thoroughly up to date with the latest research, including the latest theories and empirical properties of evolutionary computation. The Third Edition also features new knowledge-building aids. Readers will find a host of new and revised examples. New questions at the end of each chapter enable readers to test their knowledge. Intriguing assignments that prepare readers to manage challenges in industry and research have been added to the end of each chapter as well. This is a must-have reference for professionals in computer and electrical engineering; it provides them with the very latest techniques and applications in machine intelligence. With its question sets and assignments, the publication is also recommended as a graduate-level textbook. Evolutionary Computation: Toward a New Philosophy of Machine Intelligence Fogel, David B., IEEE Computer Society Press

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Evolutionary Computation - Fogel, David B.
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ID: 272211

This Third Edition provides the latest tools and techniques that enable computers to learn The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does. Readers gain an understanding of the history of evolutionary computation, which provides a foundation for the author's thorough presentation of the latest theories shaping current research. Balancing theory with practice, the author provides readers with the skills they need to apply evolutionary algorithms that can solve many of today's intransigent problems by adapting to new challenges and learning from experience. Several examples are provided that demonstrate how these evolutionary algorithms learn to solve problems. In particular, the author provides a detailed example of how an algorithm is used to evolve strategies for playing chess and checkers. As readers progress through the publication, they gain an increasing appreciation and understanding of the relationship between learning and intelligence. Readers familiar with the previous editions will discover much new and revised material that brings the publication thoroughly up to date with the latest research, including the latest theories and empirical properties of evolutionary computation. The Third Edition also features new knowledge-building aids. Readers will find a host of new and revised examples. New questions at the end of each chapter enable readers to test their knowledge. Intriguing assignments that prepare readers to manage challenges in industry and research have been added to the end of each chapter as well. This is a must-have reference for professionals in computer and electrical engineering; it provides them with the very latest techniques and applications in machine intelligence. With its question sets and assignments, the publication is also recommended as a graduate-level textbook. Technology Technology eBook, Wiley

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Hardback, [PU: John Wiley & Sons Inc], The revised and significantly expanded third edition of Evolutionary Computation presents the latest advances in the theory and practice of evolutionary computation. Highlighting the relationship between learning and intelligence, the book shows readers how to use simulated evolution to achieve machine intelligence., Artificial Intelligence

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Evolutionary Computation - David B. Fogel
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Evolutionary Computation: Toward a New Philosophy of Machine Intelligence

This Third Edition provides the latest tools and techniques that enable computers to learn The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does. Readers gain an understanding of the history of evolutionary computation, which provides a foundation for the author's thorough presentation of the latest theories shaping current research. Balancing theory with practice, the author provides readers with the skills they need to apply evolutionary algorithms that can solve many of today's intransigent problems by adapting to new challenges and learning from experience. Several examples are provided that demonstrate how these evolutionary algorithms learn to solve problems. In particular, the author provides a detailed example of how an algorithm is used to evolve strategies for playing chess and checkers. As readers progress through the publication, they gain an increasing appreciation and understanding of the relationship between learning and intelligence. Readers familiar with the previous editions will discover much new and revised material that brings the publication thoroughly up to date with the latest research, including the latest theories and empirical properties of evolutionary computation. The Third Edition also features new knowledge-building aids. Readers will find a host of newand revised examples. New questions at the end of each chapter enable readers to test their knowledge. Intriguing assignments that prepare readers to manage challenges in industry and research have been added to the end of each chapter as well. This is a must-have referenc

Detailangaben zum Buch - Evolutionary Computation: Toward a New Philosophy of Machine Intelligence


EAN (ISBN-13): 9780471669517
ISBN (ISBN-10): 0471669512
Gebundene Ausgabe
Erscheinungsjahr: 2006
Herausgeber: John Wiley & Sons
274 Seiten
Gewicht: 0,526 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 05.07.2007 12:59:13
Buch zuletzt gefunden am 19.12.2017 17:14:40
ISBN/EAN: 9780471669517

ISBN - alternative Schreibweisen:
0-471-66951-2, 978-0-471-66951-7


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