Giovanni Sartor

H. Prakken

In the study of forms of legal reasoning, logic and argumentation theory long followed separate tracks. `Legal logicians' tended to focus on a deductive reconstruction of justifying a decision, disregarding the dialectical process leading to the chosen justification. Others instead emphasized the adversarial and discretionary nature of legal reasoning, involving reasonable evaluation of alternative choices, and the use of analogical reasoning. Recently, however, developments in Artificial Intelligence and Law have paved the way for overcoming this separation. Logic has widened its scope to defensible argumentation, and informal accounts of analogy and dialectics have inspired the construction of computer programs. Thus the prospect is emerging of an integrated logical and dialectical account of legal argument, adding to the understanding of legal reasoning, and providing a formal basis for computer tools that assist and mediate legal debates while leaving room for human initiative. This book presents contributions to this development. From a logical point of view it covers topics such as evaluating conflicting arguments, weighing reasons, modelling legal disputes as a dialogue game, the role of the burden of proof, the relation between principles, rules, reasons and facts, and the relation between deductive and nondeductive arguments. Written by leading scholars in the field and building on recent developments in logic and Artificial Intelligence, the chapters provide a state-of-the-art account of research on the logical aspects of legal argument.

Logical Models of Legal Argumentation

S. Bistarelli

F. Santini

The investigation of computational models of argument is a rich and fascinating interdisciplinary research field with two ultimate aims: the theoretical goal of understanding argumentation as a cognitive phenomenon by modeling it in computer programs, and the practical goal of supporting the development of computer-based systems able to engage in argumentation-related activities with human users or among themselves. The biennial International Conferences on Computational Models of Argument (COMMA) provide a dedicated forum for the presentation and discussion of the latest advancements in the field, and cover both basic research and innovative applications. This book presents the proceedings of COMMA 2020. Due to the Covid-19 pandemic, COMMA 2020 was held as an online event on the originally scheduled dates of 8 -11 September 2020, organised by the University of Perugia, Italy. The book includes 28 full papers and 13 short papers selected from a total of 78 submissions, the abstracts of 3 invited talks and 13 demonstration abstracts. The interdisciplinary nature of the field is reflected, and contributions cover both theory and practice. Theoretical contributions include new formal models, the study of formal or computational properties of models, designs for implemented systems and experimental research. Practical papers include applications to medicine, law and criminal investigation, chatbots and online product reviews. The argument-mining trend from previous COMMA’s is continued, while an emerging trend this year is the use of argumentation for explainable AI. The book provided an overview of the latest work on computational models of argument, and will be of interest to all those working in the field.

H. Prakken

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