Compliance checking on first-order knowledge with conflicting and compensatory norms: a comparison among currently available technologies

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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
Artificial Intelligence and Law
June 2023

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 concrete LegalTech applications, in which compliance checking must be enforced on (large) sets of individuals. Furthermore, we are interested in technologies that are freely available and that can be further investigated and compared by the scientific community. In other words, this paper does not consider technologies only employed in industry and/or whose source code is non-accessible. This paper formalizes a selected use case in the considered reasoners and compares the implementations, also in terms of simulations with respect to shared synthetic datasets. The comparison will highlight that lot of further research still needs to be done to integrate the benefits featured by the different reasoners into a single standardized first-order framework, suitable for LegalTech applications. All source codes are freely available at, together with instructions to locally reproduce the simulations.

keywordsCompliance checking · First-order knowledge · LegalTech
journal or series
book Artificial Intelligence and Law (AIL)
funding project
wrenchCompuLaw — Computable Law (01/11/2019–31/10/2025)