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...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Beteilige Person: Liu, Weiru (VerfasserIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Heidelberg Physica-Verlag HD 2001
Schriftenreihe:Studies in Fuzziness and Soft Computing 77
Schlagwörter:
Links:https://doi.org/10.1007/978-3-7908-1811-6
https://doi.org/10.1007/978-3-7908-1811-6
https://doi.org/10.1007/978-3-7908-1811-6
Zusammenfassung: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
Umfang:1 Online-Ressource (XIV, 274 p)
ISBN:9783790818116
DOI:10.1007/978-3-7908-1811-6