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Reasoning about uncertainty and explicit ignorance in generalized possibilistic logic

Dubois, Didier, Prade, Henri and Schockaert, Steven 2014. Reasoning about uncertainty and explicit ignorance in generalized possibilistic logic. Presented at: 2nd European Conference on Artificial Intelligence (ECAI), Prague, Czech Republic, 18-22 August 2014. Published in: Schaub, Torsten, Friedrich, Gerhard and O'Sullivan, Barry eds. ECAI 2014: 21st European Conference on Artificial Intelligence. Frontiers in Artificial Intelligence and Applications Amsterdam: IOS Press, pp. 261-266. 10.3233/978-1-61499-419-0-261

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Abstract

Generalized possibilistic logic (GPL) is a logic for reasoning about the revealed beliefs of another agent. It is a two-tier propositional logic, in which propositional formulas are encapsulated by modal operators that are interpreted in terms of uncertainty measures from possibility theory. Models of a GPL theory represent weighted epistemic states and are encoded as possibility distributions. One of the main features of GPL is that it allows us to explicitly reason about the ignorance of another agent. In this paper, we study two types of approaches for reasoning about ignorance in GPL, based on the idea of minimal specificity and on the notion of guaranteed possibility, respectively. We show how these approaches naturally lead to different flavours of the language of GPL and a number of decision problems, whose complexity ranges from the first to the third level of the polynomial hierarchy.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: IOS Press
ISBN: 9781614994183
Last Modified: 04 Jun 2017 07:50
URI: http://orca.cf.ac.uk/id/eprint/68592

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