DDLV: A system for rational preferential reasoning for Datalog

Harrison, Michael and Meyer, Thomas (2020) DDLV: A system for rational preferential reasoning for Datalog, South African Computer Journal, 32, SAICSIT.

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Abstract

Datalog is a powerful language that can be used to represent explicit knowledge and compute inferences in knowledge bases. Datalog cannot, however, represent or reason about contradictory rules. This is a limitation as contradictions are often present in domains that contain exceptions. In this paper, we extend Datalog to repres- ent contradictory and defeasible information. We define an approach to efficiently reason about contradictory information in Datalog and show that it satisfies the KLM requirements for a rational consequence relation. We introduce DDLV, a defeasible Datalog reasoning system that implements this approach. Finally, we evaluate the performance of DDLV.

Item Type:	Journal article (online only)
Additional Information:	https://doi.org/10.18489/sacj.v32i2.850
Subjects:	Computing methodologies > Artificial intelligence > Knowledge representation and reasoning
Date Deposited:	01 Sep 2021 09:58
Last Modified:	01 Sep 2021 09:58
URI:	http://pubs.cs.uct.ac.za/id/eprint/1422

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