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Defeasible Reasoning via Datalog^neg

arXiv 2106.10946 ↗First posted 21 Jun 2021cs.LO cs.AIcited by 0

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Abstract (arXiv)

We address the problem of compiling defeasible theories to Datalog^neg programs. We prove the correctness of this compilation, for the defeasible logic DL(partial||), but the techniques we use apply to many other defeasible logics. Structural properties of DL(partial||) are identified that support efficient implementation and/or approximation of the conclusions of defeasible theories in the logic, compared with other defeasible logics. We also use previously well-studied structural properties of logic programs to adapt to incomplete Datalog^neg implementations.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 105 references that are in the map. First posted on arXiv 21 Jun 2021.

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References · 9

  1. 2017Multi-shot ASP solving with clingocited by 115
  2. 2018The Vadalog System: Datalog-based Reasoning for Knowledge Graphscited by 25
  3. 2020Rethinking Defeasible Reasoning: A Scalable Approachcited by 4
  4. 2018Scaling-Up In-Memory Datalog Processing: Observations and Techniquescited by 3
  5. 2017Annotated Defeasible Logiccited by 2
  6. 2018Scaling-Up Reasoning and Advanced Analytics on BigDatacited by 2
  7. 2019Declarative Programming for Microcontrollers -- Datalog on Arduinocited by 1
  8. 2020Formulog: Datalog for SMT-Based Static Analysis (Extended Version)cited by 1
  9. 2021On Signings and the Well-Founded Semanticscited by 1

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