Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
An introduction to possibilistic and fuzzy logics
Readings in uncertain reasoning
Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
On the consistency of defeasible databases
Artificial Intelligence
Modal logics for qualitative possibility and beliefs
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Reasoning with qualitative probabilities can be tractable
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Unifying default reasoning and belief revision in a modal framework
Artificial Intelligence
Conditional logics of normality: a modal approach
Artificial Intelligence
Relations between the logic of theory change and nonmonotonic logic
Proceedings of the Workshop on The Logic of Theory Change
System Z: a natural ordering of defaults with tractable applications to nonmonotonic reasoning
TARK '90 Proceedings of the 3rd conference on Theoretical aspects of reasoning about knowledge
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
Revision sequences and nested conditionals
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Conditional logics of normality as modal systems
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
Focusing on probable diagnoses
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
A logic for revision and subjunctive queries
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Abduction as belief revision: a model of preferred explanations
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Revision by conditional beliefs
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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We present a semantics for adding uncertainty to conditional logics for default reasoning and belief revision. We are able to treat conditional sentences as statements of conditional probability, and express rules for revision such as "If A were believed, then B would be believed to degree p." This method of revision extends conditionalization by allowing meaningful revision by sentences whose probability is zero. This is achieved through the use of counterfactual probabilities. Thus, our system accounts for the best properties of qualitative methods of update (in particular, the AGM theory of revision) and probabilistic methods. We also show how our system can be viewed as a unification of probability theory and possibility theory, highlighting their orthogonality and providing a means for expressing the probability of a possibility. We also demonstrate the connection to Lewis's method of imaging.