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Practical Methods for Constructing Possibility Distributions
Author(s) -
Dubois Didier,
Prade Henri
Publication year - 2016
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21782
Subject(s) - computer science , similarity (geometry) , scale (ratio) , interval (graph theory) , ordinal scale , mathematics , data mining , statistical physics , statistics , artificial intelligence , combinatorics , geography , physics , image (mathematics) , cartography
This survey paper provides an overview of existing methods for building possibility distributions. We both consider the case of qualitative possibility theory, where the scale remains ordinal, and the case of quantitative possibility theory, where the scale is the real interval [0, 1]. Methods may be order‐based or similarity‐based for qualitative possibility distributions, whereas statistical methods apply in the quantitative case and then possibilities encode nested random epistemic sets or upper bounds of probabilities. But distance‐based approaches, or expert estimates, may be also exploited in the quantitative case.