Sciweavers

ECAI
2006
Springer

Background Default Knowledge and Causality Ascriptions

13 years 7 months ago
Background Default Knowledge and Causality Ascriptions
A model is defined that predicts an agent's ascriptions of causality (and related notions of facilitation and justification) between two events in a chain, based on background knowledge about the normal course of the world. Background knowledge is represented by nonmonotonic consequence relations. This enables the model to handle situations of poor information, where background knowledge is not accurate enough to be represented in, e.g., structural equations. Tentative properties of causality ascriptions are explored, i.e., preference for abnormal factors, transitivity, coherence with logical entailment, and stability with respect to disjunction and conjunction. Empirical data are reported to support the psychological plausibility of our basic definitions.
Jean-François Bonnefon, Rui Da Silva Neves,
Added 22 Aug 2010
Updated 22 Aug 2010
Type Conference
Year 2006
Where ECAI
Authors Jean-François Bonnefon, Rui Da Silva Neves, Didier Dubois, Henri Prade
Comments (0)