Robot Learning (The Springer International Series in Engineering and Computer Science, 233) - Hardcover
Synopsis
Building a robot that learns to perform a task has been acknowledged as one of the major challenges facing artificial intelligence. Self-improving robots would relieve humans from much of the drudgery of programming and would potentially allow operation in environments that were changeable or only partially known. Progress towards this goal would also make fundamental contributions to artificial intelligence by furthering our understanding of how to successfully integrate disparate abilities such as perception, planning, learning and action.
Although its roots can be traced back to the late fifties, the area of robot learning has lately seen a resurgence of interest. The flurry of interest in robot learning has partly been fueled by exciting new work in the areas of reinforcement earning, behavior-based architectures, genetic algorithms, neural networks and the study of artificial life. Robot Learning gives an overview of some of the current research projects in robot learning being carried out at leading universities and research laboratories in the United States. The main research directions in robot learning covered in this book include: reinforcement learning, behavior-based architectures, neural networks, map learning, action models, navigation and guided exploration.
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Robot Learning (The Springer International Series in Engineering and Computer Science, 233)
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Building a robot that learns to perform a task has been acknowledged as one of the major challenges facing artificial intelligence. Self-improving robots would relieve humans from much of the drudgery of programming and would potentially allow operation in environments that were changeable or only partially known. Progress towards this goal would also make fundamental contributions to artificial intelligence by furthering our understanding of how to successfully integrate disparate abilities such as perception, planning, learning and action. Although its roots can be traced back to the late fifties, the area of robot learning has lately seen a resurgence of interest. The flurry of interest in robot learning has partly been fueled by exciting new work in the areas of reinforcement earning, behavior-based architectures, genetic algorithms, neural networks and the study of artificial life. Robot Learning gives an overview of some of the current research projects in robot learning being carried out at leading universities and research laboratories in the United States. The main research directions in robot learning covered in this book include: reinforcement learning, behavior-based architectures, neural networks, map learning, action models, navigation and guided exploration. 260 pp. Englisch. Seller Inventory # 9780792393658
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Building a robot that learns to perform a task has been acknowledged as one of the major challenges facing artificial intelligence. Self-improving robots would relieve humans from much of the drudgery of programming and would potentially allow operation . Seller Inventory # 5971437
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Buch. Condition: Neu. Robot Learning | J. H. Connell (u. a.) | Buch | xiii | Englisch | 1993 | Springer | EAN 9780792393658 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 101998338
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Robot Learning
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Kluwer Academic Publishers, 1993
ISBN 10: 0792393651
ISBN 13: 9780792393658
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Condition: New. An overview of some of the research projects in robot learning being carried out at research laboratories in the United States. This book covers some of the research directions in robot learning including: reinforcement learning, behavior-based architectures, neural networks, map learning, action models, navigation and guided exploration. Editor(s): Connell, Jonathan H.; Mahadevan, Sridhar. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 240 pages, biography. BIC Classification: TJFM1. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 15. Weight in Grams: 542. . 1993. Hardback. . . . . Seller Inventory # V9780792393658
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Robot Learning
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Springer US, Springer US Jun 1993, 1993
ISBN 10: 0792393651
ISBN 13: 9780792393658
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Buch. Condition: Neu. Neuware -Building a robot that learns to perform a task has been acknowledged as one of the major challenges facing artificial intelligence. Self-improving robots would relieve humans from much of the drudgery of programming and would potentially allow operation in environments that were changeable or only partially known. Progress towards this goal would also make fundamental contributions to artificial intelligence by furthering our understanding of how to successfully integrate disparate abilities such as perception, planning, learning and action.Although its roots can be traced back to the late fifties, the area of robot learning has lately seen a resurgence of interest. The flurry of interest in robot learning has partly been fueled by exciting new work in the areas of reinforcement earning, behavior-based architectures, genetic algorithms, neural networks and the study of artificial life. Robot Learning gives an overview of some of the current research projects in robot learning being carried out at leading universities and research laboratories in the United States. The main research directions in robot learning covered in this book include: reinforcement learning, behavior-based architectures, neural networks, map learning, action models, navigation and guided exploration.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch. Seller Inventory # 9780792393658
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Robot Learning
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Building a robot that learns to perform a task has been acknowledged as one of the major challenges facing artificial intelligence. Self-improving robots would relieve humans from much of the drudgery of programming and would potentially allow operation in environments that were changeable or only partially known. Progress towards this goal would also make fundamental contributions to artificial intelligence by furthering our understanding of how to successfully integrate disparate abilities such as perception, planning, learning and action. Although its roots can be traced back to the late fifties, the area of robot learning has lately seen a resurgence of interest. The flurry of interest in robot learning has partly been fueled by exciting new work in the areas of reinforcement earning, behavior-based architectures, genetic algorithms, neural networks and the study of artificial life. Robot Learning gives an overview of some of the current research projects in robot learning being carried out at leading universities and research laboratories in the United States. The main research directions in robot learning covered in this book include: reinforcement learning, behavior-based architectures, neural networks, map learning, action models, navigation and guided exploration. Seller Inventory # 9780792393658
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Robot Learning
Published by
Kluwer Academic Publishers, 1993
ISBN 10: 0792393651
ISBN 13: 9780792393658
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Condition: New. An overview of some of the research projects in robot learning being carried out at research laboratories in the United States. This book covers some of the research directions in robot learning including: reinforcement learning, behavior-based architectures, neural networks, map learning, action models, navigation and guided exploration. Editor(s): Connell, Jonathan H.; Mahadevan, Sridhar. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 240 pages, biography. BIC Classification: TJFM1. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 15. Weight in Grams: 542. . 1993. Hardback. . . . . Books ship from the US and Ireland. Seller Inventory # V9780792393658
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Robot Learning (The Springer International Series in Engineering and Computer Science, 233)
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