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Editorial introduction to the special issue
2013
Annals of Mathematics and Artificial Intelligence
The information available to intelligent agents is often uncertain, inconsistent and incomplete. It is then crucially important to develop logics for uncertainty to achieve different complex reasoning tasks. Uncertainty is present in many applications and may be represented using different frameworks: plausibility orderings, probability theory frameworks, argumentation systems, etc. This special issue gathers five contributions that cover different aspects of reasoning under uncertainty using
doi:10.1007/s10472-013-9354-x
fatcat:tags3zayhbc3zmjwzv2mr4ah54