Preferences and Similarities de Giacomo Riccia

Preferences and Similarities: CISM International Centre for Mechanical Sciences, cartea 504

Giacomo Riccia

Didier Dubois

Hans-Joachim Lenz

Rudolf Kruse

The fields of similarity and preference are still broadening due to the exploration of new fields of application. This is caused by the strong impact of vagueness, imprecision, uncertainty and dominance on human and agent information, communication, planning, decision, action, and control as well as by the technical progress of the information technology itself. The topics treated in this book are of interest to computer scientists, statisticians, operations researchers, experts in AI, cognitive psychologists and economists.

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	Preț	Express
Paperback (1)	950^.39 lei 6-8 săpt.
SPRINGER VIENNA – 19 oct 2010	950^.39 lei 6-8 săpt.
Hardback (1)	957^.06 lei 6-8 săpt.
SPRINGER VIENNA – 23 sep 2008	957^.06 lei 6-8 săpt.

Preț

Express

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950^.39 lei 6-8 săpt.

SPRINGER VIENNA – 19 oct 2010

950^.39 lei 6-8 săpt.

Hardback (1)

957^.06 lei 6-8 săpt.

SPRINGER VIENNA – 23 sep 2008

957^.06 lei 6-8 săpt.

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Cuprins

Similarity, Dominance, Fuzzy Logic and Efficiency.- Similarity of Fuzzy Sets and Dominance of Random Variables: a Quest for Transitivity.- A Logic-based View of Similarities and Preferences.- An overview of bipolar qualitative decision rules.- Uncertainty, Vagueness, Incompleteness, Truthlikeliness and Proximity.- Logical approaches to fuzzy similarity-based reasoning: an overview.- Logics of Similarity and their Dual Tableaux A Survey.- Proximities in Statistics: Similarity and Distance.- Similarity, Independence, Probability and Game Theory.- Similarity Relations and Independence Concepts.- Imprecision and Structure in Modelling Subjective Similarity.- Defensive Forecasting: How to Use Similarity to Make Forecasts That Pass Statistical Tests.- Argument-based Decision Making, Qualitative Preferences Reasoning, and Label Rankings.- Comparing decisions on the basis of a bipolar typology of arguments.- A Snapshot on Reasoning with Qualitative Preference Statements in AI.- Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants.- Constraints and Preferences: Modelling Frameworks and Multi-agent settings.