The paper investigates the relative expressiveness of two logic-based languages for reasoning over streams, namely LARS Programs - the language of the Logic-based framework for Analytic Reasoning over Streams called LARS - and LDSR - the language of the recent extension of the I-DLV system for stream reasoning called I-DLV-sr. Although these two languages build over Datalog, they do differ both in syntax and semantics. To reconcile their expressive capabilities for stream reasoning, we define a comparison framework that allows us to show that, without any restrictions, the two languages are incomparable and to identify fragments of each language that can be expressed via the other one.

A Formal Comparison between Datalog-based Languages for Stream Reasoning

Leone N.;Manna M.;Morelli M. C.;Perri S.
2022-01-01

Abstract

The paper investigates the relative expressiveness of two logic-based languages for reasoning over streams, namely LARS Programs - the language of the Logic-based framework for Analytic Reasoning over Streams called LARS - and LDSR - the language of the recent extension of the I-DLV system for stream reasoning called I-DLV-sr. Although these two languages build over Datalog, they do differ both in syntax and semantics. To reconcile their expressive capabilities for stream reasoning, we define a comparison framework that allows us to show that, without any restrictions, the two languages are incomparable and to identify fragments of each language that can be expressed via the other one.
Datalog
Knowledge Representation and Reasoning
Relative Expressiveness
Stream Reasoning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/341792
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