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  1. Law and logic: A review from an argumentation perspective.Henry Prakken & Giovanni Sartor - 2015 - Artificial Intelligence 227 (C):214-245.
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  • A crowdsourcing approach to building a legal ontology from text.Anatoly P. Getman & Volodymyr V. Karasiuk - 2014 - Artificial Intelligence and Law 22 (3):313-335.
    This article focuses on the problems of application of artificial intelligence to represent legal knowledge. The volume of legal knowledge used in practice is unusually large, and therefore the ontological knowledge representation is proposed to be used for semantic analysis, presentation and use of common vocabulary, and knowledge integration of problem domain. At the same time some features of legal knowledge representation in Ukraine have been taken into account. The software package has been developed to work with the ontology. The (...)
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  • Compliance checking on first-order knowledge with conflicting and compensatory norms: a comparison among currently available technologies.Livio Robaldo, Sotiris Batsakis, Roberta Calegari, Francesco Calimeri, Megumi Fujita, Guido Governatori, Maria Concetta Morelli, Francesco Pacenza, Giuseppe Pisano, Ken Satoh, Ilias Tachmazidis & Jessica Zangari - 2024 - Artificial Intelligence and Law 32 (2):505-555.
    This paper analyses and compares some of the automated reasoners that have been used in recent research for compliance checking. Although the list of the considered reasoners is not exhaustive, we believe that our analysis is representative enough to take stock of the current state of the art in the topic. We are interested here in formalizations at the _first-order_ level. Past literature on normative reasoning mostly focuses on the _propositional_ level. However, the propositional level is of little usefulness for (...)
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  • Cross-categorization of legal concepts across boundaries of legal systems: in consideration of inferential links.Fumiko Kano Glückstad, Tue Herlau, Mikkel N. Schmidt & Morten Mørup - 2014 - Artificial Intelligence and Law 22 (1):61-108.
    This work contrasts Giovanni Sartor’s view of inferential semantics of legal concepts with a probabilistic model of theory formation. The work further explores possibilities of implementing Kemp’s probabilistic model of theory formation in the context of mapping legal concepts between two individual legal systems. For implementing the legal concept mapping, we propose a cross-categorization approach that combines three mathematical models: the Bayesian Model of Generalization, the probabilistic model of theory formation, i.e., the Infinite Relational Model first introduced by Kemp et (...)
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  • Agreement and relational justice : a perspective from philosophy and sociology of law.Pompeu Casanovas - unknown
    Relationships between empirical and philosophical approaches to the law have not been always peaceful. Agreement seems the most natural way to build up and implementing regulations and justice within human-machine inter-faces (natural and artificial societies), and might help to bridge the gap between both theoretical approaches. Recent researches on relational law, relational jus-tice, crowdsourcing, regulatory systems and regulatory models are introduced. These concepts need further clarification, but they stand as political companions to more standard conceptions of law in the Semantic (...)
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  • A model of juridical acts: part 1: the world of law. [REVIEW]Jaap Hage - 2011 - Artificial Intelligence and Law 19 (1):23-48.
    This paper aims at providing an account of juridical acts that forms a suitable starting point for the creation of computational systems that deal with juridical acts. The paper is divided into two parts. Because juridical acts will be analyzed as intentional changes in the world of law, the ‘furniture’ of this world, that consists broadly speaking of entities, facts and rules, plays a central role in the analysis. This first part of the paper deals with this furniture and its (...)
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  • Stratification of normative systems with intermediaries.Lars Lindahl & Jan Odelstad - 2011 - Journal of Applied Logic 9 (2):113-136.
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