Learning Classifier Systems: From Foundations to Applications (Lecture Notes in Computer Science)

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9783540677291: Learning Classifier Systems: From Foundations to Applications (Lecture Notes in Computer Science)

Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This book provides a unique survey of the current state of the art of LCS and highlights some of the most promising research directions. The first part presents various views of leading people on what learning classifier systems are. The second part is devoted to advanced topics of current interest, including alternative representations, methods for evaluating rule utility, and extensions to existing classifier system models. The final part is dedicated to promising applications in areas like data mining, medical data analysis, economic trading agents, aircraft maneuvering, and autonomous robotics. An appendix comprising 467 entries provides a comprehensive LCS bibliography.

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Book Description Springer-Verlag Berlin and Heidelberg GmbH Co. KG, Germany, 2000. Paperback. Book Condition: New. 2000 ed.. 236 x 150 mm. Language: English . Brand New Book ***** Print on Demand *****.Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This book provides a unique survey of the current state of the art of LCS and highlights some of the most promising research directions. The first part presents various views of leading people on what learning classifier systems are. The second part is devoted to advanced topics of current interest, including alternative representations, methods for evaluating rule utility, and extensions to existing classifier system models. The final part is dedicated to promising applications in areas like data mining, medical data analysis, economic trading agents, aircraft maneuvering, and autonomous robotics. An appendix comprising 467 entries provides a comprehensive LCS bibliography. Bookseller Inventory # AAV9783540677291

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Book Description Springer. Paperback. Book Condition: New. This item is printed on demand. Paperback. 347 pages. Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This book provides a unique survey of the current state of the art of LCS and highlights some of the most promising research directions. The first part presents various views of leading people on what learning classifier systems are. The second part is devoted to advanced topics of current interest, including alternative representations, methods for evaluating rule utility, and extensions to existing classifier system models. The final part is dedicated to promising applications in areas like data mining, medical data analysis, economic trading agents, aircraft maneuvering, and autonomous robotics. An appendix comprising 467 entries provides a comprehensive LCS bibliography. This item ships from La Vergne,TN. Paperback. Bookseller Inventory # 9783540677291

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Lanzi, Pier Luca (Editor)/ Stolzmann, Wolfgang (Editor)/ Wilson, Stewart W. (Editor)
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Book Description Springer Verlag, 2000. Paperback. Book Condition: Brand New. 1st edition. 347 pages. 9.00x6.00x0.75 inches. In Stock. Bookseller Inventory # __3540677291

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