Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference: 2 (Atlantis Thinking Machines, 2) - Hardcover
Synopsis
The general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations. Every one of the major modes of interacting with such storehouses – querying, data mining, data analysis – is addressed by current technologies only in very limited and unsatisfactory ways. The impact of a solution to this problem would be huge and pervasive, as the domains of human pursuit to which such storehouses are acutely relevant is numerous and rapidly growing. Finally, we give a more detailed treatment of one potential solution with this class, based on our prior work with the Probabilistic Logic Networks (PLN) formalism. We show how PLN can be used to carry out realworld reasoning, by means of a number of practical examples of reasoning regarding human activities inreal-world situations.
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Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations. Every one of the major modes of interacting with such storehouses - querying, data mining, data analysis - is addressed by current technologies only in very limited and unsatisfactory ways. The impact of a solution to this problem would be huge and pervasive, as the domains of human pursuit to which such storehouses are acutely relevant is numerous and rapidly growing. Finally, we give a more detailed treatment of one potential solution with this class, based on our prior work with the Probabilistic Logic Networks (PLN) formalism. We show how PLN can be used to carry out realworld reasoning, by means of a number of practical examples of reasoning regarding human activities inreal-world situations. 280 pp. Englisch. Seller Inventory # 9789491216107
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Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The book gives the first accessible, reasonably comprehensive and unified review of the various existing approaches to any of spatial, temporal or contextual logicThe book breaks new research ground via explaining theoretically and by means of exa. Seller Inventory # 5839620
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Real-world Reasoning: The Challenge of Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference
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Hardcover. Condition: Brand New. 2011 edition. 278 pages. 9.50x6.25x0.75 inches. In Stock. Seller Inventory # 9491216104
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Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference
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Buch. Condition: Neu. Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference | Ben Goertzel (u. a.) | Buch | ix | Englisch | 2011 | Atlantis Press | EAN 9789491216107 | 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 # 106702422
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Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference
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Buch. Condition: Neu. Neuware -The general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations. Every one of the major modes of interacting with such storehouses ¿ querying, data mining, data analysis ¿ is addressed by current technologies only in very limited and unsatisfactory ways. The impact of a solution to this problem would be huge and pervasive, as the domains of human pursuit to which such storehouses are acutely relevant is numerous and rapidly growing. Finally, we give a more detailed treatment of one potential solution with this class, based on our prior work with the Probabilistic Logic Networks (PLN) formalism. We show how PLN can be used to carry out realworld reasoning, by means of a number of practical examples of reasoning regarding human activities inreal-world situations.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 280 pp. Englisch. Seller Inventory # 9789491216107
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Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference
Print on DemandSeller: AHA-BUCH GmbH, Einbeck, Germany
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations. Every one of the major modes of interacting with such storehouses - querying, data mining, data analysis - is addressed by current technologies only in very limited and unsatisfactory ways. The impact of a solution to this problem would be huge and pervasive, as the domains of human pursuit to which such storehouses are acutely relevant is numerous and rapidly growing. Finally, we give a more detailed treatment of one potential solution with this class, based on our prior work with the Probabilistic Logic Networks (PLN) formalism. We show how PLN can be used to carry out realworld reasoning, by means of a number of practical examples of reasoning regarding human activities inreal-world situations. Seller Inventory # 9789491216107
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Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference (Atlantis Thinking Machines, 2)
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Hardcover. Condition: Like New. Like New. book. Seller Inventory # ERICA80094912161046