Abstract. We present Bayesian Description Logics (BDLs): an exten-sion of Description Logics (DLs) with contextual probabilities encoded in a Bayesian network (BN). Classical DL reasoning tasks are extended to consider also the contextual and probabilistic information in BDLs. A complexity analysis of these problems shows that, for propositionally closed DLs, this extension comes without cost, while for tractable DLs the complexity is affected by the cost of reasoning in the BN.
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Knowledge representation languages invariably reflect a trade-off between expressivity and tractabil...
Abstract. We present Bayesian Description Logics (BDLs): an exten-sion of Description Logics (DLs) w...
Description Logics (DLs) that support uncertainty are not as well studied as their crisp alternative...
We introduce the new probabilistic description logic (DL) BEL, which extends the light-weight DL EL ...
Abstract. Recently, Bayesian extensions of Description Logics, and in particular the logic BEL, were...
The DL-Lite family of tractable description logics lies between the semantic web languages RDFS and ...
Abstract. We introduce the probabilistic Description Logic BEL. In BEL, axioms are required to hold ...
Abstract. The Bayesian Description Logic (BDL) BEL is a probabilistic DL, which extends the lightwei...
We study the problem of reasoning in the probabilistic De-scription Logic BEL. Using a novel structu...
It is well known that many artificial intelligence applications need to represent and reason with kn...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Description Logics (DLs) that support uncertainty are not as well studied as their crisp alternative...
Several models combining Bayesian networks with logic exist. The two most developed models are Proba...
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Knowledge representation languages invariably reflect a trade-off between expressivity and tractabil...
Abstract. We present Bayesian Description Logics (BDLs): an exten-sion of Description Logics (DLs) w...
Description Logics (DLs) that support uncertainty are not as well studied as their crisp alternative...
We introduce the new probabilistic description logic (DL) BEL, which extends the light-weight DL EL ...
Abstract. Recently, Bayesian extensions of Description Logics, and in particular the logic BEL, were...
The DL-Lite family of tractable description logics lies between the semantic web languages RDFS and ...
Abstract. We introduce the probabilistic Description Logic BEL. In BEL, axioms are required to hold ...
Abstract. The Bayesian Description Logic (BDL) BEL is a probabilistic DL, which extends the lightwei...
We study the problem of reasoning in the probabilistic De-scription Logic BEL. Using a novel structu...
It is well known that many artificial intelligence applications need to represent and reason with kn...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Description Logics (DLs) that support uncertainty are not as well studied as their crisp alternative...
Several models combining Bayesian networks with logic exist. The two most developed models are Proba...
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Knowledge representation languages invariably reflect a trade-off between expressivity and tractabil...