Automated Reasoning with Legal Entities
A research project funded by the
Grant: CORE C20/IS/14616644
AuReLeE conclusion workshop on July 15 - July 22, onlne and in presence at the DCS at Univ. of Luxembourg.
Featuring keynotes of Christoph Benzmüller (U Bamberg) and Geoff Sutcliffe (Univ. of Miami), Alexander Steen (U Greifswald) and many more.
Learn more & joinAutomated reasoning systems are symbolic AI systems for autonomously assessing the correctness of formally specified information. Such tools are provided by the user with the information to be assessed in some textual representation, and subsequently search for a formal justification of a given claim without additional guidance from the outside. Application areas include computer-assisted mathematics, knowledge discovery and processing, computer linguistics, semantic web, and software and hardware verification. As an example of such systems, so-called SAT and SMT solvers are highly successful in both research and industry, and became standard tools for various software and hardware production chains.
In legal informatics, computer systems are used for assisting professionals and public regulators for, e.g., structuring and assessing normative contents, and for improved search in large knowledge bases. In legal reasoning, a sub-field of legal informatics, a current challenge is to design and implement reasoning technology for assisting legal drafting, for conducting (semi-)automated compliance checks, and further practically relevant applications. Usually, a first step in this process is the formalization of normative structures in knowledge bases. However, the practical utilization of these valuable knowledge bases is then often quite limited. This is, to a large extent, due to the lack of suitable computational methods that would allow the assessment and mechanized utilization of the normative information compiled by these knowledge bases.
The goal of the project Automated Reasoning with Legal Entities (AuReLeE) is thus to provide effective and general means for the automation of normative reasoning processes based on legal knowledge bases. To this end, the project will design and implement a dedicated system that combines efficient decision procedures with a flexible approach to import and re-use existing knowledge bases for their employment as underlying contexts for the normative reasoning tasks. The results of AuReLeE hence allow to full utilization of the existing legal knowledge bases’ potential for compliance checking.
AuReLeE is conducted at the Faculty of Science, Technology and Medicine of the University of Luxembourg. It is hosted by the Individual and Collective Reasoning (ICR) research group at the Depart of Computer Science.
Alexander Steen (University of Greifswald, proposer of AuReLeE and PI)
David Fuenmayor (Research and development specialist)
Leon van der Torre (University of Luxembourg)
Adam Wyner (Swansea University, mentor)
All the software and code produced within the AuReLeE project is open-source
and freely available (usually under MIT or BSD-like license) at GitHub:
github.com/aureleeNet
.
Highlighted artifacts (repositories) are listed in the following.
rio is an automated reasoning system for unconstrained and constrained I/O logics based on propositional logic. It is implemented as a Scala application.
In short, the system allows you to specify a set of conditional norms and a number of inputs (each of which describing aspects of the current situational context), and provides automated means for inferring whether given obligations (also encoded as formulas) can be derived. rio can also be used to infer the set of detached obligations instead of checking detachment of given ones.
See the README for more details.
This repository collects formalizations of different logical models in the context of normative reasoning and argumentation.
Please contact Alexander Steen for questions about the project.