An Argumentation-Based Legal Reasoning Approach for DL-Ontology
This work addresses the problem of handling inconsistencies in legal ontologies for applications like autonomous vehicles, representing an incremental advancement in combining argumentation and description logics.
The paper tackles reasoning with inconsistent description logic-based legal ontologies by proposing a structured argumentation framework based on ASPIC+, and shows that this approach can derive acceptable assertions and perform traditional reasoning tasks, with a focus on autonomous vehicles in legal AI.
Ontology is a popular method for knowledge representation in different domains, including the legal domain, and description logics (DL) is commonly used as its description language. To handle reasoning based on inconsistent DL-based legal ontologies, the current paper presents a structured argumentation framework particularly for reasoning in legal contexts on the basis of ASPIC+, and translates the legal ontology into formulas and rules of an argumentation theory. With a particular focus on the design of autonomous vehicles from the perspective of legal AI, we show that using this combined theory of formal argumentation and DL-based legal ontology, acceptable assertions can be obtained based on inconsistent ontologies, and the traditional reasoning tasks of DL ontologies can also be accomplished. In addition, a formal definition of explanations for the result of reasoning is presented.