Propositional, Probabilistic and Evidential Reasoning Integrating Numerical and Symbolic Approaches

The book systematically provides the reader with a broad range of systems/research work to date that address the importance of combining numerical and symbolic approaches to reasoning under uncertainty in complex applications. It covers techniques on how to extend propositional logic to a probabilis...

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Main Author: Liu, Weiru
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Heidelberg Physica-Verlag HD 2001, 2001
Edition:1st ed. 2001
Series:Studies in Fuzziness and Soft Computing
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Summary:The book systematically provides the reader with a broad range of systems/research work to date that address the importance of combining numerical and symbolic approaches to reasoning under uncertainty in complex applications. It covers techniques on how to extend propositional logic to a probabilistic one and compares such derived probabilistic logic with closely related mechanisms, namely evidence theory, assumption based truth maintenance systems and rough sets, in terms of representing and reasoning with knowledge and evidence. The book is addressed primarily to researchers, practitioners, students and lecturers in the field of Artificial Intelligence, particularly in the areas of reasoning under uncertainty, logic, knowledge representation and reasoning, and non-monotonic reasoning
Physical Description:XIV, 274 p online resource
ISBN:9783790818116