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Paperback. Condizione: New. 1993rd.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Artificial Intelligence and cognitive science are the twofields devoted to the study and development ofknowledge-based systems (KBS). Over the past 25years,researchers have proposed several approaches for modelingknowledge in KBS, including several kinds of formalism suchas semantic networks, frames, and logics. In the early1980s, J.F. Sowa introduced the conceptual graph (CG) theorywhich provides a knowledge representation frameworkconsisting of a form of logic with a graph notationandintegrating several features from semantic net and framerepresentations. Since that time, several research teamsover the world have been working on the application andextension of CG theory in various domains ranging fromnatural language processing to database modeling and machinelearning.This volume contains selected papers fromthe internationalconference on Conceptual Structures held in the city ofQuebec, Canada, August 4-7, 1993. The volume opens withinvited papers by J.F. Sowa, B.R. Gaines, and J. Barwise.

Taschenbuch. Condizione: Neu. Conceptual Graphs for Knowledge Representation | First International Conference on Conceptual Structures, ICCS'93, Quebec City, Canada, August 4-7, 1993. Proceedings | Guy W. Mineau (u. a.) | Taschenbuch | x | Englisch | 1993 | Springer | EAN 9783540569794 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Paperback. Condizione: New. 1993rd.

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 468 | Sprache: Englisch | Produktart: Bücher | Artificial Intelligence and cognitive science are the twofields devoted to the study and development ofknowledge-based systems (KBS). Over the past 25years,researchers have proposed several approaches for modelingknowledge in KBS, including several kinds of formalism suchas semantic networks, frames, and logics. In the early1980s, J.F. Sowa introduced the conceptual graph (CG) theorywhich provides a knowledge representation frameworkconsisting of a form of logic with a graph notationandintegrating several features from semantic net and framerepresentations. Since that time, several research teamsover the world have been working on the application andextension of CG theory in various domains ranging fromnatural language processing to database modeling and machinelearning.This volume contains selected papers fromthe internationalconference on Conceptual Structures held in the city ofQuebec, Canada, August 4-7, 1993. The volume opens withinvited papers by J.F. Sowa, B.R. Gaines, and J. Barwise.

Taschenbuch. Condizione: Neu. Conceptual Structures: Logical, Linguistic, and Computational Issues | 8th International Conference on Conceptual Structures, ICCS 2000 Darmstadt, Germany, August 14-18, 2000 Proceedings | Bernhard Ganter (u. a.) | Taschenbuch | xii | Englisch | 2000 | Springer | EAN 9783540678595 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computerscientistscreatemodelsofaperceivedreality.ThroughAItechniqu es, these models aim at providing the basic support for emulating cognitive - havior such as reasoning and learning, which is one of the main goals of the AI research e ort. Such computer models are formed through the interaction of various acquisition and inference mechanisms: perception, concept learning, conceptual clustering, hypothesis testing, probabilistic inference, etc., and are represented using di erent paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models ( rst-order logic, modal logic, rule-based s- tems), virtual reality models (object systems, agent systems), probabilistic m- els(Bayesiannets,fuzzylogic),linguisticmodels(conceptualdependencygraph s, language-based representations), etc. OneofthestrengthsoftheConceptualGraph(CG)theoryisitsversatilityin terms of the representation paradigms under which it falls. It can be viewed and therefore used, under di erent representation paradigms, which makes it a p- ular choice for a wealth of applications. Its full coupling with di erent cognitive processes lead to the opening of the eld toward related research communities such as the Description Logic, Formal Concept Analysis, and Computational Linguistic communities. We now see more and more research results from one community enrich the other, laying the foundations of common philosophical grounds from which a successful synergy can emerge.

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

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Artificial Intelligence and cognitive science are the twofields devoted to the study and development ofknowledge-based systems (KBS). Over the past 25years,researchers have proposed several approaches for modelingknowledge in KBS, includ.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Artificial Intelligence and cognitive science are the twofields devoted to the study and development of knowledge-based systems (KBS). Over the past 25years, researchers have proposed several approaches for modeling knowledge in KBS, including several kinds of formalism such as semantic networks, frames, and logics. In the early 1980s, J.F. Sowa introduced the conceptual graph (CG) theory which provides a knowledge representation framework consisting of a form of logic with a graph notationand integrating several features from semantic net and frame representations. Since that time, several research teams over the world have been working on the application and extension of CG theory in various domains ranging from natural language processing to database modeling and machine learning. This volume contains selected papers fromthe international conference on Conceptual Structures held in the city of Quebec, Canada, August 4-7, 1993. The volume opens with invited papers by J.F. Sowa, B.R. Gaines, and J. Barwise.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 468 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Artificial Intelligence and cognitive science are the twofields devoted to the study and development ofknowledge-based systems (KBS). Over the past 25years,researchers have proposed several approaches for modelingknowledge in KBS, including several kinds of formalism suchas semantic networks, frames, and logics. In the early1980s, J.F. Sowa introduced the conceptual graph (CG) theorywhich provides a knowledge representation frameworkconsisting of a form of logic with a graph notationandintegrating several features from semantic net and framerepresentations. Since that time, several research teamsover the world have been working on the application andextension of CG theory in various domains ranging fromnatural language processing to database modeling and machinelearning.This volume contains selected papers fromthe internationalconference on Conceptual Structures held in the city ofQuebec, Canada, August 4-7, 1993. The volume opens withinvited papers by J.F. Sowa, B.R. Gaines, and J. Barwise. 468 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computerscientistscreatemodelsofaperceivedreality.ThroughAItechniques, these models aim at providing the basic support for emulating cognitive - havior such as reasoning and learning, which is one of the main goals of the AI research e ort. Such computer models are formed through the interaction of various acquisition and inference mechanisms: perception, concept learning, conceptual clustering, hypothesis testing, probabilistic inference, etc., and are represented using di erent paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models ( rst-order logic, modal logic, rule-based s- tems), virtual reality models (object systems, agent systems), probabilistic m- els(Bayesiannets,fuzzylogic),linguisticmodels(conceptualdependencygraphs, language-based representations), etc. OneofthestrengthsoftheConceptualGraph(CG)theoryisitsversatility in terms of the representation paradigms under which it falls. It can be viewed and therefore used, under di erent representation paradigms, which makes it a p- ular choice for a wealth of applications. Its full coupling with di erent cognitive processes lead to the opening of the eld toward related research communities such as the Description Logic, Formal Concept Analysis, and Computational Linguistic communities. We now see more and more research results from one community enrich the other, laying the foundations of common philosophical grounds from which a successful synergy can emerge. 588 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Computerscientistscreatemodelsofaperceivedreality.ThroughAItechniques, these models aim at providing the basic support for emulating cognitive - havior such as reasoning and learning, which is one of the main goals of the AI research e?ort. Such computer mo.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Computerscientistscreatemodelsofaperceivedreality.ThroughAItechniques, these models aim at providing the basic support for emulating cognitive - havior such as reasoning and learning, which is one of the main goals of the AI research e ort. Such computer models are formed through the interaction of various acquisition and inference mechanisms: perception, concept learning, conceptual clustering, hypothesis testing, probabilistic inference, etc., and are represented using di erent paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models ( rst-order logic, modal logic, rule-based s- tems), virtual reality models (object systems, agent systems), probabilistic m- els(Bayesiannets,fuzzylogic),linguisticmodels(conceptualdependencygraphs, language-based representations), etc. OneofthestrengthsoftheConceptualGraph(CG)theoryisitsversatilityin terms of the representation paradigms under which it falls. It can be viewed and therefore used, under di erent representation paradigms, which makes it a p- ular choice for a wealth of applications. Its full coupling with di erent cognitive processes lead to the opening of the eld toward related research communities such as the Description Logic, Formal Concept Analysis, and Computational Linguistic communities. We now see more and more research results from one community enrich the other, laying the foundations of common philosophical grounds from which a successful synergy can emerge.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 588 pp. Englisch.