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artificial intelligenceOrganisation
It is well known that many artificial intelligence applications need to represent and reason with knowledge that is not fully certain. This has motivated the study of many knowledge representation formalisms that can effectively han-dle uncertainty, and in particular probabilistic description logics (DLs) [7–9]
The DL-Lite family of tractable description logics lies between the semantic web languages RDFS and ...
[EN]The purpose of this workshop is to promote logical foundations for reasoning and learning under ...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
Logic-based knowledge representation is one of the main building blocks of (logic-based) artificial ...
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 ...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Given the complexity of the domains for which we would like to use computers as reasoning engines, ...
Abstract:-Possibilistic logic and Bayesian networks have provided advantageous methodologies and tec...
Although probabilistic knowledge representations and probabilistic reasoning have by now secured the...
Abstract. Although probabilistic knowledge representations and probabilistic reasoning have by now s...
Abstract. Representing uncertain information is crucial for modeling real world domains. In this pap...
Knowledge representation languages invariably reflect a trade-off between expressivity and tractabil...
The DL-Lite family of tractable description logics lies between the semantic web languages RDFS and ...
[EN]The purpose of this workshop is to promote logical foundations for reasoning and learning under ...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
Logic-based knowledge representation is one of the main building blocks of (logic-based) artificial ...
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 ...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Given the complexity of the domains for which we would like to use computers as reasoning engines, ...
Abstract:-Possibilistic logic and Bayesian networks have provided advantageous methodologies and tec...
Although probabilistic knowledge representations and probabilistic reasoning have by now secured the...
Abstract. Although probabilistic knowledge representations and probabilistic reasoning have by now s...
Abstract. Representing uncertain information is crucial for modeling real world domains. In this pap...
Knowledge representation languages invariably reflect a trade-off between expressivity and tractabil...
The DL-Lite family of tractable description logics lies between the semantic web languages RDFS and ...
[EN]The purpose of this workshop is to promote logical foundations for reasoning and learning under ...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
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