Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Institutions: abstract model theory for specification and programming
Journal of the ACM (JACM)
The uncertain reasoner's companion: a mathematical perspective
The uncertain reasoner's companion: a mathematical perspective
Moving Between Logical Systems
Selected papers from the 11th Workshop on Specification of Abstract Data Types Joint with the 8th COMPASS Workshop on Recent Trends in Data Type Specification
Using Institutions for the Study of Qualitative and Quantitative Conditional Logics
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
The Semantics of CLEAR, A Specification Language
Proceedings of the Abstract Software Specifications, 1979 Copenhagen Winter School
The relationship of the logic of big-stepped probabilities to standard probabilistic logics
FoIKS'10 Proceedings of the 6th international conference on Foundations of Information and Knowledge Systems
Semantical investigations into nonmonotonic and probabilistic logics
Annals of Mathematics and Artificial Intelligence
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We show how probabilistic logic and probabilistic conditional logic can be formalized in the framework of institutions, thereby supporting the study of structural properties of both syntax and semantics of these logics. By using the notions of institution morphism and institution embedding, the relationships between probabilistic propositional logic, probabilistic conditional logic, and the underlying two-valued propositional logic are investigated in detail, telling us, for instance, precisely how to interpret probabilistic conditionals as probabilistic facts or in a propositional setting and vice versa.