Enabling reasoning with LegalRuleML. Issue 1 (14th September 2018)

• Record Type: Journal Article
• Authors: LAM, HO-PUN; HASHMI, MUSTAFA
• Is Part Of: Theory and practice of logic programming. Volume 19:Issue 1(2019)
• Page Start: 1
• Page End: 26
• Publication Date: 2018-09-14
• Subjects: Deontic logic, -- modal defeasible logic, -- legal reasoning, -- LegalRuleML, -- business contracts; Logic programming -- Periodicals; Artificial intelligence -- Computer programs -- Periodicals; Constraint programming (Computer science) -- Periodicals; 005.115
• DOI: 10.1017/S1471068418000339
• Languages: English
• ISSNs: 1471-0684

Abstract

Abstract: In order to automate verification process, regulatory rules written in natural language need to be translated into a format that machines can understand. However, none of the existing formalisms can fully represent the elements that appear in legal norms. For instance, most of these formalisms do not provide features to capture the behavior of deontic effects, which is an important aspect in automated compliance checking. This paper presents an approach for transforming legal norms represented using legalruleml to a variant of modal defeasible logic (and vice versa) such that a legal statement represented using LegalRuleML can be transformed into a machine-readable format that can be understood and reasoned about depending upon the client's preferences.