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  1. 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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  • Thirty years of Artificial Intelligence and Law: the first decade. [REVIEW]Guido Governatori, Trevor Bench-Capon, Bart Verheij, Michał Araszkiewicz, Enrico Francesconi & Matthias Grabmair - 2022 - Artificial Intelligence and Law 30 (4):481-519.
    The first issue of _Artificial Intelligence and Law_ journal was published in 1992. This paper provides commentaries on landmark papers from the first decade of that journal. The topics discussed include reasoning with cases, argumentation, normative reasoning, dialogue, representing legal knowledge and neural networks.
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  • Thirty years of artificial intelligence and law: the third decade.Serena Villata, Michal Araszkiewicz, Kevin Ashley, Trevor Bench-Capon, L. Karl Branting, Jack G. Conrad & Adam Wyner - 2022 - Artificial Intelligence and Law 30 (4):561-591.
    The first issue of Artificial Intelligence and Law journal was published in 1992. This paper offers some commentaries on papers drawn from the Journal’s third decade. They indicate a major shift within Artificial Intelligence, both generally and in AI and Law: away from symbolic techniques to those based on Machine Learning approaches, especially those based on Natural Language texts rather than feature sets. Eight papers are discussed: two concern the management and use of documents available on the World Wide Web, (...)
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  • Formalizing commitments using the event calculus and RuleML.Joost de Kruijff & Hans Weigand - forthcoming - Applied ontology:1-26.
    Smart Contracts enable the automated execution of exchanges on the blockchain. From an ontological perspective, smart contracts create and automate the fulfillment of social commitments between actors. Whereas traditional deontic logic is used to make a legal determination in contractual multi-actor interactions, this paper focuses on the consequences of these actions resulting from that determination, thereby shifting the focus from monitoring to execution. The interactions between actors and the consequences in terms of commitments have not yet been formalized for smart (...)
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  • Contract as automaton: representing a simple financial agreement in computational form.Mark D. Flood & Oliver R. Goodenough - 2022 - Artificial Intelligence and Law 30 (3):391-416.
    We show that the fundamental legal structure of a well-written financial contract follows a state-transition logic that can be formalized mathematically as a finite-state machine (specifically, a deterministic finite automaton or DFA). The automaton defines the states that a financial relationship can be in, such as “default,” “delinquency,” “performing,” etc., and it defines an “alphabet” of events that can trigger state transitions, such as “payment arrives,” “due date passes,” etc. The core of a contract describes the rules by which different (...)
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