Gradual Semantics for Weighted Bipolar SETAFs

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An explainable approach to deducing outcomes in european court of human rights cases using ADFs

In this paper we present an argumentation-based approach to representing and reasoning about a domain of law that has previously been addressed through a machine learning approach. The domain concerns cases that all fall within the remit of a specific Article within the European Court of Human Rights. We perform a comparison between the approaches, based on two criteria: ability of the model to accurately replicate the decision that was made in the real life legal cases within the particular domain, and the quality of the explanation provided by the models. Our initial results show that the system based on the argumentation approach improves on the machine learning results in terms of accuracy, and can explain its outcomes in terms of the issue on which the case turned, and the factors that were crucial in arriving at the conclusion

An Environment for Possibilistic Logic Programming Based on Dung Semantics

In this paper, we present a tool for possibilistic logic programming.This tool is a desktop-based, stand-alone application that assists a user in creating, editing and querying a possibly inconsistent possibilistic program. The tool computes all the arguments emerging from the program, the grounded extension based on Dung-style semantics, and it is capable of showing arguments and grounded extensions graphically. The language for programs is enriched with pragmas for allowing the user to con gure labels for necessity degrees, deciding if using transposes of strict rules, performing consistency checks within arguments, and appeal to the use of accrual of rules for building arguments. We describe its usage, architectural elements and we also provide experimental evaluation of its performance.Sociedad Argentina de Informática e Investigación Operativ

Examining the Modelling Capabilities of Defeasible Argumentation and non-Monotonic Fuzzy Reasoning

Knowledge-representation and reasoning methods have been extensively researched within Artificial Intelligence. Among these, argumentation has emerged as an ideal paradigm for inference under uncertainty with conflicting knowledge. Its value has been predominantly demonstrated via analyses of the topological structure of graphs of arguments and its formal properties. However, limited research exists on the examination and comparison of its inferential capacity in real-world modelling tasks and against other knowledge-representation and non-monotonic reasoning methods. This study is focused on a novel comparison between defeasible argumentation and non-monotonic fuzzy reasoning when applied to the representation of the ill-defined construct of human mental workload and its assessment. Different argument-based and non-monotonic fuzzy reasoning models have been designed considering knowledge-bases of incremental complexity containing uncertain and conflicting information provided by a human reasoner. Findings showed how their inferences have a moderate convergent and face validity when compared respectively to those of an existing baseline instrument for mental workload assessment, and to a perception of mental workload self-reported by human participants. This confirmed how these models also reasonably represent the construct under consideration. Furthermore, argument-based models had on average a lower mean squared error against the self-reported perception of mental workload when compared to fuzzy-reasoning models and the baseline instrument. The contribution of this research is to provide scholars, interested in formalisms on knowledge-representation and non-monotonic reasoning, with a novel approach for empirically comparing their inferential capacity

Interpretation, argumentation, and the determinacy of law

Published online: 14 July 2023This article models legal interpretation through argumentation and provides a logical analysis of interpretive arguments, their conflicts, and the resulting indeterminacies. Interpretive arguments are modelled as defeasible inferences, which can be challenged and defeated by counterarguments and be reinstated through further arguments. It is shown what claims are possibly (defensibly) or necessarily (justifiably) supported by the arguments constructible from a given interpretive basis, i.e., a set of interpretive canons coupled with reasons for their application. It is finally established under what conditions such arguments provide single outcomes or rather support alternative interpretive conclusions, thus leading to propositions of law whose truth-value is undetermined

In memoriam Douglas N. Walton: the influence of Doug Walton on AI and law

Doug Walton, who died in January 2020, was a prolific author whose work in informal logic and argumentation had a profound influence on Artificial Intelligence, including Artificial Intelligence and Law. He was also very interested in interdisciplinary work, and a frequent and generous collaborator. In this paper seven leading researchers in AI and Law, all past programme chairs of the International Conference on AI and Law who have worked with him, describe his influence on their work

Argumentation Schemes for Clinical Decision Support

This paper demonstrates how argumentation schemes can be used in decision support systems that help clinicians in making treatment decisions. The work builds on the use of computational argumentation, a rigorous approach to reasoning with complex data that places strong emphasis on being able to justify and explain the decisions that are recommended. The main contribution of the paper is to present a novel set of specialised argumentation schemes that can be used in the context of a clinical decision support system to assist in reasoning about what treatments to offer. These schemes provide a mechanism for capturing clinical reasoning in such a way that it can be handled by the formal reasoning mechanisms of formal argumentation. The paper describes how the integration between argumentation schemes and formal argumentation may be carried out, sketches how this is achieved by an implementation that we have created, and illustrates the overall process on a small set of case studies

Joint attacks and accrual in argumentation frameworks

While modelling arguments, it is often useful to represent joint attacks, i.e., cases where multiple arguments jointly attack another (note that this is different from the case where multiple arguments attack another in isolation). Based on this remark, the notion of joint attacks has been proposed as a useful extension of classical Abstract Argumentation Frameworks, and has been shown to constitute a genuine extension in terms of expressive power. In this chapter, we review various works considering the notion of joint attacks from various perspectives, including abstract and structured frameworks. Moreover, we present results detailing the relation among frameworks with joint attacks and classical argumentation frameworks, computational aspects, and applications of joint attacks. Last but not least, we propose a roadmap for future research on the subject, identifying gaps in current research and important research directions.Fil: Bikakis, Antonis. University College London; Estados UnidosFil: Cohen, Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Dvoák, Wolfgang. Technische Universitat Wien; AustriaFil: Flouris, Giorgos. Foundation for Research and Technology; GreciaFil: Parsons, Simon. University of Lincoln; Reino Unid

Modelling accrual of arguments in ASPIC+

In this paper a new formal model of argument accrual is proposed as an adaptation of the ASPIC+ framework for structured argumentation. The new model aims to overcome several weaknesses of existing proposals. It is shown to have desirable formal properties that are in line with standard work on formal argumentation, and to be applicable to a range of situations in legal reasoning