A logic to reason about likelihood
Artificial Intelligence
Likelihood, probability, and knowledge
Computational Intelligence
Artificial intelligence and mathematical theory of computation
Reasoning about knowledge and probability
Journal of the ACM (JACM)
Modeling belief in dynamic systems, part I: foundations
Artificial Intelligence
Reasoning about noisy sensors and effectors in the situation calculus
Artificial Intelligence
Reasoning about Information Change
Journal of Logic, Language and Information
A modal analysis of possibility theory
FAIR '91 Proceedings of the International Workshop on Fundamentals of Artificial Intelligence Research
The logic of public announcements, common knowledge, and private suspicions
TARK '98 Proceedings of the 7th conference on Theoretical aspects of rationality and knowledge
Multi-agent Logics of Dynamic Belief and Knowledge
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
A Modal Analysis of Possibility Theory
ECSQAU Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
A Logic for Planning under Partial Observability
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A fuzzy modal logic for belief functions
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Reasoning about noisy sensors in the situation calculus
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
The frame problem and knowledge-producing actions
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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We investigate a modal logic of probability with a unary modal operator expressing that a proposition is more probable than its negation. Such an operator is not closed under conjunction, and its modal logic is therefore non-normal. Within this framework we study the relation of probability with other modal concepts: belief and action. We focus on the evolution of belief, and propose an integration of revision. For that framework we give a regression algorithm.