mlsanityData to 14 Oct 2026

A Formal Comparison between Datalog-based Languages for Stream Reasoning (extended version)

arXiv 2208.12726 ↗First posted 26 Aug 2022cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 21 references that are in the map. First posted on arXiv 26 Aug 2022.

Builds on

6 of 21 references.

References · 6

  1. 2019ASP-Core-2 Input Language Formatcited by 77
  2. 2017Expressive Stream Reasoning with Lasercited by 7
  3. 2019A Distributed Approach to LARS Stream Reasoning (System paper)cited by 4
  4. 2020Incremental maintenance of overgrounded logic programs with tailored simplificationscited by 3
  5. 2013Answer Set Programming for Stream Reasoningcited by 2
  6. 2021I-DLV-sr: A Stream Reasoning System based on I-DLVcited by 2

Built on by

Not cited yet.