A decidable propositional dynamic logic with explicit probabilities
Information and Control
A logic for reasoning about probabilities
Information and Computation - Selections from 1988 IEEE symposium on logic in computer science
An analysis of first-order logics of probability
Artificial Intelligence
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Reasoning about knowledge and probability
Journal of the ACM (JACM)
Decidability and expressiveness for first-order logics of probability
Information and Computation
Errata: “The relationship between knowledge, belief, and certainty”
Annals of Mathematics and Artificial Intelligence
It Usually Works: The Temporal Logic of Stochastic Systems
Proceedings of the 7th International Conference on Computer Aided Verification
Bisimulation for Labelled Markov Processes
LICS '97 Proceedings of the 12th Annual IEEE Symposium on Logic in Computer Science
Conditional Probability Meets Update Logic
Journal of Logic, Language and Information
Weakly complete axiomatization of exogenous quantum propositional logic
Information and Computation
Probabilistic temporal logics via the modal mu-calculus
Theoretical Computer Science
Discrete Linear-time Probabilistic Logics: Completeness, Decidability and Complexity
Journal of Logic and Computation
A branching time logic with two types of probability operators
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
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We introduce a probabilistic modal logic PPL extending the work of [Ronald Fagin, Joseph Y. Halpern, and Nimrod Megiddo. A logic for reasoning about probabilities. Information and Computation, 87(1,2):78-128, 1990; Ronald Fagin and Joseph Y. Halpern. Reasoning about knowledge and probability. Journal of the ACM, 41(2):340-367, 1994] by allowing arbitrary nesting of a path probabilistic operator and we prove its completeness. We prove that our logic is strictly more expressive than other logics such as the logics cited above. By considering a probabilistic extension of CTL we show that this additional expressive power is really needed in some applications.