Technical Report on the Learning of Case Relevance in Case-Based Reasoning with Abstract Argumentation

Case-based reasoning is known to play an important role in several legal settings. In this paper we focus on a recent approach to case-based reasoning, supported by an instantiation of abstract argumentation whereby arguments represent cases and attack between arguments results from outcome disagreement between cases and a notion of relevance. In this context, relevance is connected to a form of specificity among cases. We explore how relevance can be learnt automatically in practice with the help of decision trees, and explore the combination of case-based reasoning with abstract argumentation (AA-CBR) and learning of case relevance for prediction in legal settings. Specifically, we show that, for two legal datasets, AA-CBR and decision-tree-based learning of case relevance perform competitively in comparison with decision trees. We also show that AA-CBR with decision-tree-based learning of case relevance results in a more compact representation than their decision tree counterparts, which could be beneficial for obtaining cognitively tractable explanations

Present and Future of Formal Argumentation

This report documents the program and the outcomes of Dagstuhl Perspectives Workshop 15362 “Present and Future of Formal Argumentation”. The goal of this Dagstuhl Perspectives Workshop was to gather the world leading experts in formal argumentation in order to develop a SWOT (Strength, Weaknesses, Opportunities, Threats) analysis of the current state of the research in this field and to draw accordingly some strategic lines to ensure its successful development in the future. A critical survey of the field has been carried out through individual presentations and collective discussions. Moreover, working group activity lead to identify several open problems in argumentation

Formal argumentation and epistemic logic: what can they do for each other?

Arguing and believing are two central cognitive dimensions of both human beings and artificial intelligent agents. The interrelation of these two notions (or groups of notions) is at the root of classic debates in epistemology and argumentation theory. During this talk, we will critically review recent literature on combining two well-known families of formalisms that account respectively for argumentation and beliefs, these are, formal argumentation and epistemic logic. [...]Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Can Artificial Intelligence Interprete Legal Norms? A Problem of Practical Reason

La formalización del razonamiento jurídico y, específicamente, de la interpretación es un viejo sueño de nuestra cultura. Hoy, la Inteligencia Artificial parece lista para cumplir esa tarea. Teóricos computacionales y lógicos están desarrollando herramientas técnicas para estructurar modelos formales de interpretación jurídica útiles para la Inteligencia Artificial. Sin embargo, estos esfuerzos han conseguido sólo formalizaciones abstractas, que no son capaces de resolver cuestiones materiales sobre la respuesta correcta ante un caso nuevo. Los algoritmos no pueden descubrir, ni evaluar, problemas humanos sin la ayuda de programadores; no pueden decidir entre hipótesis interpretativas alternativas; en fin, la Inteligencia Artificial no puede cumplir con las exigencias de la razón práctica en el derecho.The formalization of legal reasoning and, specifically, of legal interpretation is an old dream of our culture. Today, Artificial Intelligence seems ready to comply with this task. Computational theorist and logicians are developing technical tools to structure formal models of legal interpretations useful to IA. However, these efforts have reached only abstract formalizations, but these do not have capabilities to resolve material questions about the correct answer in front of a new case. Algorithms cannot discover, nor evaluate, human problems without the help of programmers; they cannot decide between alternative interpretive hypothesis. At last, IA can not comply with exigencies of practical reason in law

Semi-Abstract Value-Based Argumentation Framework

In his seminal paper, Phan Minh Dung (1995) proposed abstract argumentation framework, which models argumentation using directed graphs where structureless arguments are the nodes and attacks among the arguments are the edges. In the following years, many extensions of this framework were introduced. These extensions typically add a certain form of structure to the arguments. This thesis showcases two such extensions -- value-based argumentation framework by Trevor Bench-Capon (2002) and semi-abstract argumentation framework by Esther Anna Corsi and Christian Ferm\"uller (2017). The former introduces a mapping function that links individual arguments to a set of ordered values, enabling a distinction between objectively and subjectively acceptable arguments. The latter links claims of individual arguments to propositional formulae and then applies newly-introduced attack principles in order to make implicit attacks explicit and to enable a definition of a consequence relation that relies on neither the truth values nor the interpretations in the usual sense. The contribution of this thesis is two-fold. Firstly, the new semi-abstract value-based argumentation framework is introduced. This framework maps propositional formulae associated with individual arguments to a set of ordered values. Secondly, a complex moral dilemma is formulated using the original and the value-based argumentation frameworks showcasing the expressivity of these formalisms.Comment: Submitted as a Bachelor Thesis at TU Wien on 2019-11-07. Advisor: Christian Ferm\"uller. 49 page