Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The logical view of conditioning and its application to possibility and evidence theories
International Journal of Approximate Reasoning
Epistemic entrenchment and possibilistic logic
Artificial Intelligence
Evidence, knowledge, and belief functions
International Journal of Approximate Reasoning - Special issue: The belief functions revisited: questions and answers
Updating Uncertain Information
IPMU '90 Proceedings of the 3rd International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems: Uncertainty in Knowledge Bases
Updating with belief functions, ordinal conditional functions and possibility measures
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Belief revision with uncertain inputs in the possibilistic setting
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Jeffrey's rule of conditioning in a possibilistic framework
Annals of Mathematics and Artificial Intelligence
Possibility theory for reasoning about uncertain soft constraints
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Syntactic computation of hybrid possibilistic conditioning under uncertain inputs
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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The difference between Bayesian conditioning and Lewis' imaging is somewhat similar to the one between Gardenfors' belief revision and Katsuno and Mendelzon' updating in the logical framework. Counterparts in possibility theory of these two operations are presented, including the case of conditioning upon an uncertain observation. Possibilistic conditioning satisfies all the postulates for belief revision, and possibilistic imaging all the updating postulates. Lastly, a third operation called "focusing" is naturally introduced in the setting of belief and plausibility functions.