Abstract
This paper describes a decision support system to represent the semantics of legal norms. The focus is on designing and software-technical implementing of a comprehensive system to support model based reasoning on legal norms and enabling end-users to create, maintain, and analyze semantic models, i.e. ontologies, representing structure and semantics of norms.
A model based expression language (MxL) has been developed to coherently support the formalization of logical and arithmetical operations. MxL is intended to define complex, nested, strongly-typed, and functional operations. The paper summarizes research on the design and implementation of a legal expert system built upon model based decision structures. Thereby, three different components, namely a model store, a model execution component, and an interaction component have been developed. The formalization, execution, and analysis is shown on German child benefit regulations.
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Waltl, B., Reschenhofer, T., Matthes, F. (2018). Modeling, Execution and Analysis of Formalized Legal Norms in Model Based Decision Structures. In: Pagallo, U., Palmirani, M., Casanovas, P., Sartor, G., Villata, S. (eds) AI Approaches to the Complexity of Legal Systems. AICOL AICOL AICOL AICOL AICOL 2015 2016 2016 2017 2017. Lecture Notes in Computer Science(), vol 10791. Springer, Cham. https://doi.org/10.1007/978-3-030-00178-0_10
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