Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Attributive concept descriptions with complements
Artificial Intelligence
A probabilistic terminological logic for modelling information retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Decision Support Systems - Special issue on logic modeling
On the relative expressiveness of description logics and predicate logics
Artificial Intelligence
An Introduction to Variational Methods for Graphical Models
Machine Learning
Artificial Intelligence
Learning Probabilistic Models of Relational Structure
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Semantics and Inference for Recursive Probability Models
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
P-SHOQ(D): A Probabilistic Extension of SHOQ(D) for Probabilistic Ontologies in the Semantic Web
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Convergence Results for Relational Bayesian Networks
LICS '98 Proceedings of the 13th Annual IEEE Symposium on Logic in Computer Science
Reasoning about Uncertainty
Market Analysis Using a Combination of Bayesian Networks and Description Logics
Market Analysis Using a Combination of Bayesian Networks and Description Logics
Machine Learning
The Description Logic Handbook
The Description Logic Handbook
ACM Transactions on Computational Logic (TOCL)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Expressive probabilistic description logics
Artificial Intelligence
Approximate algorithms for credal networks with binary variables
International Journal of Approximate Reasoning
Probabilistic logic with independence
International Journal of Approximate Reasoning
First-Order Probabilistic Languages: Into the Unknown
Inductive Logic Programming
PR-OWL: A Framework for Probabilistic Ontologies
Proceedings of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006)
MPE and partial inversion in lifted probabilistic variable elimination
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Lifted first-order belief propagation
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
First-order probabilistic inference
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A correspondence theory for terminological logics: preliminary report
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Lifted first-order probabilistic inference
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
BLOG: probabilistic models with unknown objects
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Loopy belief propagation for approximate inference: an empirical study
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Discriminative probabilistic models for relational data
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Object-oriented Bayesian networks
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Can OWL and logic programming live together happily ever after?
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Learning terminologies in probabilistic description logics
SBIA'10 Proceedings of the 20th Brazilian conference on Advances in artificial intelligence
Semantic mapping with a probabilistic description logic
SBIA'10 Proceedings of the 20th Brazilian conference on Advances in artificial intelligence
Learning probabilistic description logics: a framework and algorithms
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
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This paper introduces a probabilistic description logic that adds probabilistic inclusions to the popular logic $\mathcal{ALC}$, and derives inference algorithms for inference in the logic. The probabilistic logic, referred to as cr$\mathcal{ALC}$ ("credal" $\mathcal{ALC}$), combines the usual acyclicity condition with a Markov condition; in this context, inference is equated with calculation of (bounds on) posterior probability in relational credal/Bayesian networks. As exact inference does not seem scalable due to the presence of quantifiers, we present first-order loopy propagation methods that seem to behave appropriately for non-trivial domain sizes.