Defeasible Reasoning via Datalog$^\neg$
Fuente:
arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2021
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| _version_ | 1866909296064724992 |
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| author | Maher, Michael J. |
| author_facet | Maher, Michael J. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2106_10946 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Defeasible Reasoning via Datalog$^\neg$ Maher, Michael J. Logic in Computer Science Artificial Intelligence 03B70 (Primary) 03B60, 03B53 (Secondary) I.2.3; F.4.1; I.2.2; I.2.4 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. |
| title | Defeasible Reasoning via Datalog$^\neg$ |
| topic | Logic in Computer Science Artificial Intelligence 03B70 (Primary) 03B60, 03B53 (Secondary) I.2.3; F.4.1; I.2.2; I.2.4 |
| url | https://arxiv.org/abs/2106.10946 |