Abstract. We introduce the probabilistic Description Logic BEL. In BEL, axioms are required to hold only in an associated context. The probabilistic component of the logic is given by a Bayesian network that describes the joint probability distribution of the contexts. We study the main reasoning problems in this logic; in particular, we (i) prove that deciding positive and almost-sure entailments is not harder for BEL than for the BN, and (ii) show how to compute the probability, and the most likely context for a consequence.
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...
Description logics in their standard setting only allow for representing and reasoning with crisp kn...
We propose a general scheme for adding probabilistic reasoning capabilities to a wide variety of kno...
We introduce the new probabilistic description logic (DL) BEL, which extends the light-weight DL EL ...
We study the problem of reasoning in the probabilistic De-scription Logic BEL. Using a novel structu...
Abstract. Recently, Bayesian extensions of Description Logics, and in particular the logic BEL, were...
Abstract. The Bayesian Description Logic (BDL) BEL is a probabilistic DL, which extends the lightwei...
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...
Description Logics (DLs) that support uncertainty are not as well studied as their crisp alternative...
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
The DL-Lite family of tractable description logics lies between the semantic web languages RDFS and ...
I examine the idea of incorporating probability into logic for a logic of practical reasoning. I int...
A significant part of current research on (inductive) logic programming deals with probabilistic log...
Uncertainty is a fundamental and irreducible aspect of our knowledge about the world. Probability is...
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...
Description logics in their standard setting only allow for representing and reasoning with crisp kn...
We propose a general scheme for adding probabilistic reasoning capabilities to a wide variety of kno...
We introduce the new probabilistic description logic (DL) BEL, which extends the light-weight DL EL ...
We study the problem of reasoning in the probabilistic De-scription Logic BEL. Using a novel structu...
Abstract. Recently, Bayesian extensions of Description Logics, and in particular the logic BEL, were...
Abstract. The Bayesian Description Logic (BDL) BEL is a probabilistic DL, which extends the lightwei...
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...
Description Logics (DLs) that support uncertainty are not as well studied as their crisp alternative...
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
The DL-Lite family of tractable description logics lies between the semantic web languages RDFS and ...
I examine the idea of incorporating probability into logic for a logic of practical reasoning. I int...
A significant part of current research on (inductive) logic programming deals with probabilistic log...
Uncertainty is a fundamental and irreducible aspect of our knowledge about the world. Probability is...
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...
Description logics in their standard setting only allow for representing and reasoning with crisp kn...
We propose a general scheme for adding probabilistic reasoning capabilities to a wide variety of kno...