Legal reasoning in answer set programming

Aravanis, T; Demiris, K; Peppas, P

Legal reasoning in answer set programming

Aravanis, T Demiris, K Peppas, P

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Publication Type:: Conference Proceeding
Citation:: Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, 2018, 2018-November pp. 302 - 306
Issue Date:: 2018-12-13

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Field	Value	Language
dc.contributor.author	Aravanis, T	en_US
dc.contributor.author	Demiris, K	en_US
dc.contributor.author	Peppas, P https://orcid.org/0000-0002-0008-5505	en_US
dc.date.issued	2018-12-13	en_US
dc.identifier.citation	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, 2018, 2018-November pp. 302 - 306	en_US
dc.identifier.isbn	9781538674499	en_US
dc.identifier.issn	1082-3409	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133577
dc.description.abstract	© 2018 IEEE. Answer Set Programming is a declarative problem solving approach, initially tailored to modelling problems in the area of Knowledge Representation and Reasoning. In this article, we provide a knowledge-based system, capable of representing and reasoning about legal knowledge in the context of Answer Set Programming-thus, modelling non-monotonicity that is inherent in legal arguments. The work, although limited to a specific indicative domain, namely, university regulations, has a variety of extensions. The overall approach constitutes a representative implementation of the Answer Set Programming's modelling methodology, as well as an enhancing of the bond between Artificial Intelligence and Legal Science, bringing us a step closer to a successful development of an automated legal reasoning system for real-world applications.	en_US
dc.relation.ispartof	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI	en_US
dc.relation.isbasedon	10.1109/ICTAI.2018.00055	en_US
dc.title	Legal reasoning in answer set programming	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2018-November	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2018-November	en_US

Abstract:

© 2018 IEEE. Answer Set Programming is a declarative problem solving approach, initially tailored to modelling problems in the area of Knowledge Representation and Reasoning. In this article, we provide a knowledge-based system, capable of representing and reasoning about legal knowledge in the context of Answer Set Programming-thus, modelling non-monotonicity that is inherent in legal arguments. The work, although limited to a specific indicative domain, namely, university regulations, has a variety of extensions. The overall approach constitutes a representative implementation of the Answer Set Programming's modelling methodology, as well as an enhancing of the bond between Artificial Intelligence and Legal Science, bringing us a step closer to a successful development of an automated legal reasoning system for real-world applications.

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http://hdl.handle.net/10453/133577