Artificial Intelligence
A logic for reasoning about probabilities
Information and Computation - Selections from 1988 IEEE symposium on logic in computer science
Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
Anytime deduction for probabilistic logic
Artificial Intelligence
Probabilistic logic programming with conditional constraints
ACM Transactions on Computational Logic (TOCL)
Probabilistic Reasoning Under Coherence in System P
Annals of Mathematics and Artificial Intelligence
Maude: specification and programming in rewriting logic
Theoretical Computer Science - Rewriting logic and its applications
Restricted Delta-Trees and Reduction Theorems in Multiple-Valued Logics
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
A logic for reasoning about the probability of fuzzy events
Fuzzy Sets and Systems
An anytime deduction algorithm for the probabilistic logic and entailment problems
International Journal of Approximate Reasoning
Revising imprecise probabilistic beliefs in the framework of probabilistic logic programming
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
A logic for reasoning about upper probabilities
Journal of Artificial Intelligence Research
A syntax-based framework for merging imprecise probabilistic logic programs
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Discussion: From imprecise to granular probabilities
Fuzzy Sets and Systems
Automated generation of contrapuntal musical compositions using probabilistic logic in Derive
Mathematics and Computers in Simulation
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A new probabilistic logic for handling imprecise probabilities is introduced, implemented in a rewriting system, and used to carry out an experiment. Each well-formed formula of the probabilistic logic is labeled with two values that represent possible minimum and maximum probabilities associated with the event related to the unlabeled formula. The aim of this logic is to facilitate application of rules to obtain an approximation of the probability interval associated with an event, without the necessity of knowing the precise probability of other events. The logic is described as a formal theory by means of its language, semantics and a proof theory. The soundness of the proof theory has been proven. Rewriting techniques are a powerful method for testing the behavior of a formal proof calculus through translation of calculus inference rules into rewrite rules. Implementation of the logic rules in a rewriting language such as Maude allows an automated reasoning system to be easily obtained, which can be consulted by applications. We developed a small game application and an experiment to test the application.