Peer-Reviewed Journal Details
Mandatory Fields
Wilson, N;
International Journal of Approximate Reasoning
Extending uncertainty formalisms to linear constraints and other complex formalisms
Optional Fields
possibilistic logic lattice-valued possibilistic logic Dempster-Shafer theory assumption-based reasoning linear constraints spatial and temporal reasoning POSSIBILISTIC LOGIC NETWORKS
Linear constraints occur naturally in many reasoning problems and the information that they represent is often uncertain. There is a difficulty in applying AI uncertainty formalisms to this situation, as their representation of the underlying logic, either as a mutually exclusive and exhaustive set of possibilities, or with a propositional or a predicate logic, is inappropriate (or at least unhelpful). To overcome this difficulty, we express reasoning with linear constraints as a logic, and develop the formalisms based on this different underlying logic. We focus in particular on a possibilistic logic representation of uncertain linear constraints, a lattice-valued possibilistic logic, an assumption-based reasoning formalism and a Dempster-Shafer representation, proving some fundamental results for these extended systems. Our results on extending uncertainty formalisms also apply to a very general class of underlying monotonic logics. (c) 2007 Published by Elsevier Inc.
DOI 10.1016/j.ijar.2007.08.007
Grant Details