Enabling Reasoning with LegalRuleML
| Autor: | Mustafa Hashmi, Ho-Pun Lam |
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| Rok vydání: | 2017 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Logic in Computer Science Computer Science - Artificial Intelligence Process (engineering) Computer science 02 engineering and technology computer.software_genre Theoretical Computer Science Artificial Intelligence Order (exchange) 020204 information systems 0202 electrical engineering electronic engineering information engineering Statement (computer science) Programming language Deontic logic F.4.2 F.1.1 Defeasible logic Rotation formalisms in three dimensions Logic in Computer Science (cs.LO) Modal Artificial Intelligence (cs.AI) Computational Theory and Mathematics Hardware and Architecture 020201 artificial intelligence & image processing computer Software Natural language |
| DOI: | 10.48550/arxiv.1711.06128 |
| Popis: | 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. Comment: 25 pages. Under consideration for publication in Theory and Practice of Logic Programming (TPLP) |
| Databáze: | OpenAIRE |
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