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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments: ECAI'96 Workshop LDAIS, Budapest, Hungary, August 13, ... (Lecture Notes in Artificial Intelligence) - Softcover
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The complexity of systems studied in distributed artificial intelligence (DAI), such as multi-agent systems, often makes it extremely difficult or even impossible to correctly and completely specify their behavioral repertoires and dynamics. There is broad agreement that such systems should be equipped with the ability to learn in order to improve their future performance autonomously. The interdisciplinary cooperation of researchers from DAI and machine learning (ML) has established a new and very active area of research and development enjoying steadily increasing attention from both communities. This state-of-the-art report documents current and ongoing developments in the area of learning in DAI systems. It is indispensable reading for anybody active in the area and will serve as a valuable source of information.
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The complexity of systems studied in distributed artificial intelligence (DAI), such as multi-agent systems, often makes it extremely difficult or even impossible to correctly and completely specify their behavioral repertoires and dynamics. There is broad agreement that such systems should be equipped with the ability to learn in order to improve their future performance autonomously. The interdisciplinary cooperation of researchers from DAI and machine learning (ML) has established a new and very active area of research and development enjoying steadily increasing attention from both communities. This state-of-the-art report documents current and ongoing developments in the area of learning in DAI systems. It is indispensable reading for anybody active in the area and will serve as a valuable source of information.
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments: ECAI'96 Workshop LDAIS, Budapest, Hungary, August 13, . Notes in Computer Science, 1221, Band 1221)
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Zustand: Gut. 1997. 312 Seiten Anderes Cover. Von 1997. Innerhalb Deutschlands Versand je nach Größe/Gewicht als Großbrief bzw. Bücher- und Warensendung mit der Post oder per DHL. Rechnung mit MwSt.-Ausweis liegt jeder Lieferung bei. Sprache: Englisch Gewicht in Gramm: 408 Taschenbuch, Größe: 15.5 x 1.8 x 23.5 cm. Bestandsnummer des Verkäufers 935257
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments
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Springer Berlin Heidelberg, 1997
ISBN 10: 3540629343
ISBN 13: 9783540629344
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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The complexity of systems studied in distributed artificial intelligence (DAI), such as multi-agent systems, often makes it extremely difficult or even impossible to correctly and completely specify their behavioral repertoires and dynamics. There is broad . Bestandsnummer des Verkäufers 4896133
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments
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Springer Berlin Heidelberg Apr 1997, 1997
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ISBN 13: 9783540629344
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The complexity of systems studied in distributed artificial intelligence (DAI), such as multi-agent systems, often makes it extremely difficult or even impossible to correctly and completely specify their behavioral repertoires and dynamics. There is broad agreement that such systems should be equipped with the ability to learn in order to improve their future performance autonomously. The interdisciplinary cooperation of researchers from DAI and machine learning (ML) has established a new and very active area of research and development enjoying steadily increasing attention from both communities. This state-of-the-art report documents current and ongoing developments in the area of learning in DAI systems. It is indispensable reading for anybody active in the area and will serve as a valuable source of information. 312 pp. Englisch. Bestandsnummer des Verkäufers 9783540629344
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments : ECAI'96 Workshop LDAIS, Budapest, Hungary, August 13, 1996, ICMAS'96 Workshop LIOME, Kyoto, Japan, December 10, 1996 Selected Papers
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The complexity of systems studied in distributed artificial intelligence (DAI), such as multi-agent systems, often makes it extremely difficult or even impossible to correctly and completely specify their behavioral repertoires and dynamics. There is broad agreement that such systems should be equipped with the ability to learn in order to improve their future performance autonomously. The interdisciplinary cooperation of researchers from DAI and machine learning (ML) has established a new and very active area of research and development enjoying steadily increasing attention from both communities. This state-of-the-art report documents current and ongoing developments in the area of learning in DAI systems. It is indispensable reading for anybody active in the area and will serve as a valuable source of information. Bestandsnummer des Verkäufers 9783540629344
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments
Verlag:
Springer Berlin Heidelberg Apr 1997, 1997
ISBN 10: 3540629343
ISBN 13: 9783540629344
Neu
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Taschenbuch. Zustand: Neu. Neuware -The complexity of systems studied in distributed artificial intelligence (DAI), such as multi-agent systems, often makes it extremely difficult or even impossible to correctly and completely specify their behavioral repertoires and dynamics. There is broad agreement that such systems should be equipped with the ability to learn in order to improve their future performance autonomously. The interdisciplinary cooperation of researchers from DAI and machine learning (ML) has established a new and very active area of research and development enjoying steadily increasing attention from both communities. This state-of-the-art report documents current and ongoing developments in the area of learning in DAI systems. It is indispensable reading for anybody active in the area and will serve as a valuable source of information.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 312 pp. Englisch. Bestandsnummer des Verkäufers 9783540629344
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments: ECAI'96 Workshop LDAIS, Budapest, Hungary, August 13, ... (Lecture Notes in Computer Science, 1221)
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments: ECAI'96 Workshop LDAIS, Budapest, Hungary, August 13, . Papers (Lecture Notes in Computer Science)
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