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Learning and Coordination: Enhancing Agent Performance through Distributed Decision Making - Couverture souple
Synopsis
Intelligent systems of the natural kind are adaptive and robust: they learn over time and degrade gracefully under stress. If artificial systems are to display a similar level of sophistication, an organizing framework and operating principles are required to manage the resulting complexity of design and behavior.
This book presents a general framework for adaptive systems. The utility of the comprehensive framework is demonstrated by tailoring it to particular models of computational learning, ranging from neural networks to declarative logic.
The key to robustness lies in distributed decision making. An exemplar of this strategy is the neural network in both its biological and synthetic forms. In a neural network, the knowledge is encoded in the collection of cells and their linkages, rather than in any single component. Distributed decision making is even more apparent in the case of independent agents. For a population of autonomous agents, their proper coordination may well be more instrumental for attaining their objectives than are their individual capabilities.
This book probes the problems and opportunities arising from autonomous agents acting individually and collectively. Following the general framework for learning systems and its application to neural networks, the coordination of independent agents through game theory is explored. Finally, the utility of game theory for artificial agents is revealed through a case study in robotic coordination.
Given the universality of the subjects -- learning behavior and coordinative strategies in uncertain environments -- this book will be of interest to students and researchers in various disciplines, ranging from all areas of engineering to the computing disciplines; from the life sciences to the physical sciences; and from the management arts to social studies.
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Learning and Coordination
Edité par
Springer Netherlands, 2012
ISBN 10 : 9401044422
ISBN 13 : 9789401044424
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Intelligent systems of the natural kind are adaptive and robust: they learn over time and degrade gracefully under stress. If artificial systems are to display a similar level of sophistication, an organizing framework and operating principles are requir. N° de réf. du vendeur 5831230
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Learning and Coordination: Enhancing Agent Performance through Distributed Decision Making (Intelligent Systems, Control and Automation: Science and Engineering)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Learning and Coordination
Edité par
Springer Netherlands Okt 2012, 2012
ISBN 10 : 9401044422
ISBN 13 : 9789401044424
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Intelligent systems of the natural kind are adaptive and robust: they learn over time and degrade gracefully under stress. If artificial systems are to display a similar level of sophistication, an organizing framework and operating principles are required to manage the resulting complexity of design and behavior. This book presents a general framework for adaptive systems. The utility of the comprehensive framework is demonstrated by tailoring it to particular models of computational learning, ranging from neural networks to declarative logic. The key to robustness lies in distributed decision making. An exemplar of this strategy is the neural network in both its biological and synthetic forms. In a neural network, the knowledge is encoded in the collection of cells and their linkages, rather than in any single component. Distributed decision making is even more apparent in the case of independent agents. For a population of autonomous agents, their proper coordination may well be more instrumental for attaining their objectives than are their individual capabilities. This book probes the problems and opportunities arising from autonomous agents acting individually and collectively. Following the general framework for learning systems and its application to neural networks, the coordination of independent agents through game theory is explored. Finally, the utility of game theory for artificial agents is revealed through a case study in robotic coordination. Given the universality of the subjects -- learning behavior and coordinative strategies in uncertain environments -- this book will be of interest to students and researchers in various disciplines, ranging from all areas of engineering to the computing disciplines; from the life sciences to the physical sciences; and from the management arts to social studies. 204 pp. Englisch. N° de réf. du vendeur 9789401044424
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Learning and Coordination : Enhancing Agent Performance through Distributed Decision Making
Edité par
Springer Netherlands, Springer Netherlands, 2012
ISBN 10 : 9401044422
ISBN 13 : 9789401044424
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Intelligent systems of the natural kind are adaptive and robust: they learn over time and degrade gracefully under stress. If artificial systems are to display a similar level of sophistication, an organizing framework and operating principles are required to manage the resulting complexity of design and behavior. This book presents a general framework for adaptive systems. The utility of the comprehensive framework is demonstrated by tailoring it to particular models of computational learning, ranging from neural networks to declarative logic. The key to robustness lies in distributed decision making. An exemplar of this strategy is the neural network in both its biological and synthetic forms. In a neural network, the knowledge is encoded in the collection of cells and their linkages, rather than in any single component. Distributed decision making is even more apparent in the case of independent agents. For a population of autonomous agents, their proper coordination may well be more instrumental for attaining their objectives than are their individual capabilities. This book probes the problems and opportunities arising from autonomous agents acting individually and collectively. Following the general framework for learning systems and its application to neural networks, the coordination of independent agents through game theory is explored. Finally, the utility of game theory for artificial agents is revealed through a case study in robotic coordination. Given the universality of the subjects -- learning behavior and coordinative strategies in uncertain environments -- this book will be of interest to students and researchers in various disciplines, ranging from all areas of engineering to the computing disciplines; from the life sciences to the physical sciences; and from the management arts to social studies. N° de réf. du vendeur 9789401044424
Quantité disponible : 1 disponible(s)
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Learning and Coordination
Edité par
Springer Netherlands, Springer Netherlands Okt 2012, 2012
ISBN 10 : 9401044422
ISBN 13 : 9789401044424
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Intelligent systems of the natural kind are adaptive and robust: they learn over time and degrade gracefully under stress. If artificial systems are to display a similar level of sophistication, an organizing framework and operating principles are required to manage the resulting complexity of design and behavior.This book presents a general framework for adaptive systems. The utility of the comprehensive framework is demonstrated by tailoring it to particular models of computational learning, ranging from neural networks to declarative logic.The key to robustness lies in distributed decision making. An exemplar of this strategy is the neural network in both its biological and synthetic forms. In a neural network, the knowledge is encoded in the collection of cells and their linkages, rather than in any single component. Distributed decision making is even more apparent in the case of independent agents. For a population of autonomous agents, their proper coordination may well be more instrumental for attaining their objectives than are their individual capabilities.This book probes the problems and opportunities arising from autonomous agents acting individually and collectively. Following the general framework for learning systems and its application to neural networks, the coordination of independent agents through game theory is explored. Finally, the utility of game theory for artificial agents is revealed through a case study in robotic coordination.Given the universality of the subjects -- learning behavior and coordinative strategies in uncertain environments -- this book will be of interest to students and researchers in various disciplines, ranging from all areas of engineering to the computing disciplines; from the life sciences to the physical sciences; and from the management arts to social studies.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 204 pp. Englisch. N° de réf. du vendeur 9789401044424
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Learning and Coordination: Enhancing Agent Performance through Distributed Decision Making (Intelligent Systems, Control and Automation: Science and Engineering)
Vendeur : California Books, Miami, FL, Etats-Unis
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Learning and Coordination
Vendeur : Books Puddle, New York, NY, Etats-Unis
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Etat : New. pp. 206 Index. N° de réf. du vendeur 26142336889
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Learning and Coordination: Enhancing Agent Performance through Distributed Decision Making (Intelligent Systems, Control and Automation: Science and Engineering)
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Etat : New. N° de réf. du vendeur ABLIING23Apr0412070054585
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Learning and Coordination
impression à la demandeVendeur : Majestic Books, Hounslow, Royaume-Uni
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Etat : New. Print on Demand pp. 206. N° de réf. du vendeur 135027878
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Learning and Coordination
impression à la demandeVendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Etat : New. PRINT ON DEMAND pp. 206. N° de réf. du vendeur 18142336883
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