Overview
- Gives a "semantic" treatment of vague concepts in AI emphasizing the operational interpretation of the measures proposed
- Brings a new perspective on modeling vague concepts by focusing on the decision problem associated with identifying which labels can be appropriately use to describe a particular instance
- Provides a coherent theory of the probability of vague expressions useful when incorporating such descriptions into high-level models
- Demonstrates how this framework can be applied in data analysis to infer effective and informative models
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 12)
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Table of contents (8 chapters)
Keywords
About this book
Authors and Affiliations
Bibliographic Information
Book Title: Modelling and Reasoning with Vague Concepts
Authors: Jonathan Lawry
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/0-387-30262-X
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag US 2006
Hardcover ISBN: 978-0-387-29056-0Published: 11 January 2006
Softcover ISBN: 978-1-4899-8605-4Published: 25 November 2014
eBook ISBN: 978-0-387-30262-1Published: 17 June 2006
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XXV, 246
Topics: Theory of Computation, Artificial Intelligence, Complexity, Pattern Recognition, Information and Communication, Circuits, Probability and Statistics in Computer Science