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Modelling and Reasoning with Vague Concepts
Langbeschreibung
Vagueness is central to the flexibility and robustness of natural language descriptions. Vague concepts are robust to the imprecision of our perceptions, while still allowing us to convey useful, and sometimes vital, information. The study of vagueness in Artificial Intelligence (AI) is therefore motivated by the desire to incorporate this robustness and flexibility into intelligent computer systems. Such a goal, however, requires a formal model of vague concepts that will allow us to quantify and manipulate the uncertainty resulting from their use as a means of passing information between autonomous agents.
Hauptbeschreibung
Gives a "semantic" treatment of vague concepts in AI emphasizing the operational interpretation of the measures proposed
Inhaltsverzeichnis
Vague Concepts and Fuzzy Sets.- Label Semantics.- Multi-Dimensional and Multi-Instance Label Semantics.- Information from Vague Concepts.- Learning Linguistic Models from Data.- Fusing Knowledge and Data.- Non-Additive Appropriateness Measures.
ISBN-13:
9780387290560
Veröffentl:
2006
Erscheinungsdatum:
11.01.2006
Seiten:
246
Autor:
Jonathan Lawry
Gewicht:
598 g
Format:
244x164x22 mm
Sprache:
Englisch