Proceedings:
Book One
Volume
Issue:
Proceedings of the AAAI Conference on Artificial Intelligence, 20
Track:
Student Abstracts
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Abstract:
Defeasible reasoning is a rule-based approach for efficient reasoning with incomplete and inconsis-tent information. Such reasoning is, among others, useful for ontology integration, where conflicting information arises naturally; and for the modeling of business rules and policies, where rules with ex-ceptions are often used. This paper describes these scenarios in more detail, and reports on the imple-mentation of a system for defeasible reasoning on the Web. The system (a) is syntactically compati-ble with RuleML; (b) features strict and defeasible rules, priorities and two kinds of negation; (c) is based on a translation to logic programming with declarative semantics; (d) is flexible and adaptable to different intuitions within defeasible reasoning; and (e) can reason with rules, RDF, RDF Schema and (parts of) OWL ontologies.
AAAI
Proceedings of the AAAI Conference on Artificial Intelligence, 20