Default reasoning in semantic networks: a formalization of recognition and inheritance
Artificial Intelligence
Reasoning and revision in hybrid representation systems
Reasoning and revision in hybrid representation systems
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Uncertainty and vagueness in knowledge based systems
Uncertainty and vagueness in knowledge based systems
Attributive concept descriptions with complements
Artificial Intelligence
A symbolic approach to reasoning with linguistic quantifiers
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Towards precision of probabilistic bounds propagation
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
An empirical analysis of terminological representation systems
Artificial Intelligence
Imprecise Quantifiers and Conditional Probabilities
ECSQAU Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
A Hybrid Approach for Modeling Uncertainty in Terminological Logics
ECSQAU Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Generalizing term subsumption languages to fuzzy logic
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
A hybrid framework for representing uncertain knowledge
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
The future of knowledge representation
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
On scene interpretation with description logics
Image and Vision Computing
Ambient intelligence: A survey
ACM Computing Surveys (CSUR)
A complete calculus for possibilistic logic programming with fuzzy propositional variables
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Extended fuzzy ALCN and its tableau algorithm
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
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
Cooperative situation assessment in a maritime scenario
International Journal of Intelligent Systems
Probabilistic reasoning in DL-lite
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
A formal semantics for weighted ontology mappings
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
Query answering under probabilistic uncertainty in Datalog+ / - ontologies
Annals of Mathematics and Artificial Intelligence
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On the one hand, classical terminological knowledge representation excludes the possibility of handling uncertain concept descriptions involving, e.g., "usually true" concept properties, generalized quantifiers, or exceptions. On the other hand, purely numerical approaches for handling uncertainty in general axe unable to consider terminological knowledge. This paper presents the language ACCP which is a probabilistic extension of terminological logics and aims at closing the gap between the two areas of research. We present the formal semantics underlying the language ACCP and introduce the probabilistic formalism that is based on classes of probabilities and is realized by means of probabilistic constraints. Besides infering implicitly existent probabilistic relationships, the constraints guarantee terminological and probabilistic consistency. Altogether, the new language ACCP applies to domains where both term descriptions and uncertainty have to be handled.