Conditionals Information Inference (17 results)

Paperback. Condition: Very Good. Ex-library paperback in very nice condition with the usual markings and attachments. Except for library markings, interior clean and unmarked. Tight binding.

Condition: New. In.

PF. Condition: New.

Condition: New.

Condition: New.

Condition: New. pp. 236.

23,5 x 15,5 cm. Condition: Gut. 1. Auflage. XII, 218 Seiten International Workshop WCII 2002; Hagen Germany, May 2002 Revised Selected Papers. Innen sauberer, guter Zustand. Softcover, Broschur mit den üblichen Bibliotheks-Markierungen, Stempeln und Einträgen, innen wie außen, siehe Bilder. (Evtl. auch Kleber- und/oder Etikettenreste, sowie -abdrücke durch abgelöste Bibliotheksschilder). Lecture Notes in Artificial Intelligence 3301 DE-110-02 Sprache: Deutsch Gewicht in Gramm: 366.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Conditionals are fascinating and versatile objects of knowledge representation. On the one hand, they may express rules in a very general sense, representing, for example, plausible relationships, physical laws, and social norms. On the other hand, as default rules or general implications, they constitute a basic tool for reasoning, even in the presence of uncertainty. In this sense, conditionals are intimately connected both to information and inference. Due to their non-Boolean nature, however, conditionals are not easily dealt with. They are not simply true or false - rather, a conditional 'if A then B' provides a context, A, for B to be plausible (or true) and must not be confused with 'A entails B' or with the material implication 'not A or B.' This ill- trates how conditionals represent information, understood in its strict sense as reduction of uncertainty. To learn that, in the context A, the proposition B is plausible, may reduce uncertainty about B and hence is information. The ab- ity to predict such conditioned propositions is knowledge and as such (earlier) acquired information. The rst work on conditional objects dates back to Boole in the 19th c- tury, and the interest in conditionals was revived in the second half of the 20th century, when the emerging Arti cial Intelligence made claims for appropriate formaltoolstohandle'generalizedrules.'Sincethen,conditionalshavebeenthe topic of countless publications, each emphasizing their relevance for knowledge representation, plausible reasoning, nonmonotonic inference, and belief revision.

Taschenbuch. Condition: Neu. Conditionals, Information, and Inference | International Workshop, WCII 2002, Hagen, Germany, May 13-15, 2002, Revised Selected Papers | Gabriele Kern-Isberner (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2005 | Springer | EAN 9783540253327 | Verantwortliche Person für die EU: Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg, productsafety[at]springernature[dot]com | Anbieter: preigu.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condition: As New. Unread book in perfect condition.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Conditionals are fascinating and versatile objects of knowledge representation. On the one hand, they may express rules in a very general sense, representing, for example, plausible relationships, physical laws, and social norms. On the other hand, as default rules or general implications, they constitute a basic tool for reasoning, even in the presence of uncertainty. In this sense, conditionals are intimately connected both to information and inference. Due to their non-Boolean nature, however, conditionals are not easily dealt with. They are not simply true or false - rather, a conditional 'if A then B' provides a context, A, for B to be plausible (or true) and must not be confused with 'A entails B' or with the material implication 'not A or B.' This ill- trates how conditionals represent information, understood in its strict sense as reduction of uncertainty. To learn that, in the context A, the proposition B is plausible, may reduce uncertainty about B and hence is information. The ab- ity to predict such conditioned propositions is knowledge and as such (earlier) acquired information. The rst work on conditional objects dates back to Boole in the 19th c- tury, and the interest in conditionals was revived in the second half of the 20th century, when the emerging Arti cial Intelligence made claims for appropriate formaltoolstohandle'generalizedrules.'Sincethen,conditionalshavebeenthe topic of countless publications, each emphasizing their relevance for knowledge representation, plausible reasoning, nonmonotonic inference, and belief revision. 236 pp. Englisch.

Condition: New. Print on Demand pp. 236 Illus.

Condition: New. PRINT ON DEMAND pp. 236.

Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Includes supplementary material: sn.pub/extrasConditionals are fascinating and versatile objects of knowledge representation. On the one hand, they may express rules in a very general sense, representing, for example, plausible relationships, phy.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Conditionals are fascinating and versatile objects of knowledge representation. On the one hand, they may express rules in a very general sense, representing, for example, plausible relationships, physical laws, and social norms. On the other hand, as default rules or general implications, they constitute a basic tool for reasoning, even in the presence of uncertainty. In this sense, conditionals are intimately connected both to information and inference. Due to their non-Boolean nature, however, conditionals are not easily dealt with. They are not simply true or false ¿ rather, a conditional ¿if A then B¿ provides a context, A, for B to be plausible (or true) and must not be confused with ¿A entails B¿ or with the material implication ¿not A or B.¿ This ill- trates how conditionals represent information, understood in its strict sense as reduction of uncertainty. To learn that, in the context A, the proposition B is plausible, may reduce uncertainty about B and hence is information. The ab- ity to predict such conditioned propositions is knowledge and as such (earlier) acquired information. The rst work on conditional objects dates back to Boole in the 19th c- tury, and the interest in conditionals was revived in the second half of the 20th century, when the emerging Arti cial Intelligence made claims for appropriate formaltoolstohandle¿generalizedrules.¿Sincethen,conditionalshavebeenthe topic of countless publications, each emphasizing their relevance for knowledge representation, plausible reasoning, nonmonotonic inference, and belief revision.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 236 pp. Englisch.