A probabilistic deontic argumentation framework

Régis Riveret: Conceptualization, Formal analysis, Validation, Writing - original draft, Writing - review & editing. Nir Oren: Validation, Writing - original draft, Writing - review & editing. Giovanni Sartor: Conceptualization, Validation, Writing - original draft, Writing - review & editing.Peer reviewedPostprin

Handling Norms in Multi-Agent System by Means of Formal Argumentation

International audienceFormal argumentation is used to enrich and analyse normative multi-agent systems in various ways. In this chapter, we discuss three examples from the literature of handling norms by means of formal argumentation. First, we discuss how existing ways to resolve conflicts among norms using priorities can be represented in formal argumentation, by showing that the so-called Greedy and Reduction approaches can be represented using the weakest and the last link principles respectively. Based on such representation results, formal argumentation can be used to explain the detachment of obligations and permissions from hierarchical normative systems in a new way. Second, we discuss how formal argumentation can be used as a general theory for developing new approaches for normative reasoning, using a dynamic ASPIC-based legal argumentation theory. We show how existing logics of normative systems can be used to analyse such new argumentation systems. Third, we show how argumentation can be used to reason about other challenges in the area of normative multiagent systems as well, by discussing a model for arguing about legal interpretation. In particular, we show how fuzzy logic combined with formal argumentation can be used to reason about the adoption of graded categories and thus address the problem of open texture in normative interpretation. Our aim to discuss these three examples is to inspire new applications of formal argumentation to the challenges of normative reasoning in multiagent systems

Arguing about constitutive and regulative norms

Formal arguments are often represented by (support, conclusion) pairs, but in this paper we consider normative arguments represented by sequences of (brute, institutional, deontic) triples, where constitutive norms derive institutional facts from brute facts, and regulative norms derive deontic facts like obligations and permissions from institutional facts. The institutional facts may be seen as the reasons explaining or warranting the deontic obligations and permissions, and therefore they can be attacked by other normative arguments too. We represent different aspects of normative reasoning by different kinds of consistency checks among these triples, and we use formal argumentation theory to resolve conflicts among such normative arguments. In particular, we introduce various requirements for arguing about norms concerning violations, contrary-to-duty obligations, dilemmas, conflict resolution and different kinds of norms, and we introduce a formal argumentation theory satisfying the requirements. In order to illustrate our framework, we introduce a running example based on university regulations for prospective and actual students

Logics for AI and Law: Joint Proceedings of the Third International Workshop on Logics for New-Generation Artificial Intelligence and the International Workshop on Logic, AI and Law, September 8-9 and 11-12, 2023, Hangzhou

This comprehensive volume features the proceedings of the Third International Workshop on Logics for New-Generation Artificial Intelligence and the International Workshop on Logic, AI and Law, held in Hangzhou, China on September 8-9 and 11-12, 2023. The collection offers a diverse range of papers that explore the intersection of logic, artificial intelligence, and law. With contributions from some of the leading experts in the field, this volume provides insights into the latest research and developments in the applications of logic in these areas. It is an essential resource for researchers, practitioners, and students interested in the latest advancements in logic and its applications to artificial intelligence and law