-
58Handbook of Legal Reasoning and Argumentation (edited book)Springer Verlag. 2011.This handbook offers a deep analysis of the main forms of legal reasoning and argumentation from both a logical-philosophical and legal perspective. These forms are covered in an exhaustive and critical fashion, and the handbook accordingly divides in three parts: the first one introduces and discusses the basic concepts of practical reasoning. The second one discusses the main general forms of reasoning and argumentation relevant for legal discourse. The third one looks at their application in …Read more
-
170A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law (review)Artificial Intelligence and Law 20 (3): 215-319. 2012.We provide a retrospective of 25 years of the International Conference on AI and Law, which was first held in 1987. Fifty papers have been selected from the thirteen conferences and each of them is described in a short subsection individually written by one of the 24 authors. These subsections attempt to place the paper discussed in the context of the development of AI and Law, while often offering some personal reactions and reflections. As a whole, the subsections build into a history of the l…Read more
-
307Evidence & decision making in the law: theoretical, computational and empirical approachesArtificial Intelligence and Law 28 (1): 1-5. 2020.
-
248Evidential ReasoningIn G. Bongiovanni, Don Postema, A. Rotolo, G. Sartor, C. Valentini & D. Walton (eds.), Handbook in Legal Reasoning and Argumentation, Springer. pp. 447-493. 2011.The primary aim of this chapter is to explain the nature of evidential reasoning, the characteristic difficulties encountered, and the tools to address these difficulties. Our focus is on evidential reasoning in criminal cases. There is an extensive scholarly literature on these topics, and it is a secondary aim of the chapter to provide readers the means to find their way in historical and ongoing debates.
-
54Douglas Walton: Argument Evaluation and Evidence: Springer, 2016, 286 pp (review)Argumentation 32 (2): 301-307. 2018.
-
75In memoriam Douglas N. Walton: the influence of Doug Walton on AI and lawArtificial Intelligence and Law 28 (3): 281-326. 2020.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.
-
9Arguments, rules and cases in law: Resources for aligning learning and reasoning in structured domainsArgument and Computation 14 (2): 235-243. 2023.This paper provides a formal description of two legal domains. In addition, we describe the generation of various artificial datasets from these domains and explain the use of these datasets in previous experiments aligning learning and reasoning. These resources are made available for the further investigation of connections between arguments, cases and rules. The datasets are publicly available at https://github.com/CorSteging/LegalResources.
-
104Strong admissibility for abstract dialectical frameworksArgument and Computation 13 (3): 249-289. 2022.dialectical frameworks have been introduced as a formalism for modeling argumentation allowing general logical satisfaction conditions and the relevant argument evaluation. Different criteria used to settle the acceptance of arguments are called semantics. Semantics of ADFs have so far mainly been defined based on the concept of admissibility. However, the notion of strongly admissible semantics studied for abstract argumentation frameworks has not yet been introduced for ADFs. In the current wo…Read more
-
47Thirty years of Artificial Intelligence and Law: the first decade (review)Artificial Intelligence and Law 30 (4): 481-519. 2022.The first issue of _Artificial Intelligence and Law_ journal was published in 1992. This paper provides commentaries on landmark papers from the first decade of that journal. The topics discussed include reasoning with cases, argumentation, normative reasoning, dialogue, representing legal knowledge and neural networks.
-
15Towards an inclusive, responsible and sustainable open access modelArgument and Computation 13 (1): 1-2. 2022.
-
16Arguing on the Toulmin Model: New Essays in Argument Analysis and Evaluation (edited book)Springer. 2006.In The Uses of Argument, Stephen Toulmin proposed a model for the layout of arguments: claim, data, warrant, qualifier, rebuttal, backing. Since then, Toulmin’s model has been appropriated, adapted and extended by researchers in speech communications, philosophy and artificial intelligence. This book assembles the best contemporary reflection in these fields, extending or challenging Toulmin’s ideas in ways that make fresh contributions to the theory of analysing and evaluating arguments.
-
115How much does it help to know what she knows you know? An agent-based simulation studyArtificial Intelligence 200 (C): 67-92. 2013.
-
7Artificial argument assistants for defeasible argumentationArtificial Intelligence 150 (1-2): 291-324. 2003.
-
1Proceedings of the 3rd European Conference on Argumentation (edited book)College Publications. 2020.
-
Reason to Dissent. Proceedings of the 3rd European Conference on Argumentation (edited book)College Publications. 2020.
-
Reason to Dissent: Proceedings of the 3rd European Conference on Argumentation, Vol. III (edited book)College Publications+. 2020.
-
1Reason to Dissent. Proceedings of the 3rd European Conference on Argumentation, Vol. II (edited book)College Publications. 2020.
-
76Artificial intelligence as law (review)Artificial Intelligence and Law 28 (2): 181-206. 2020.Information technology is so ubiquitous and AI’s progress so inspiring that also legal professionals experience its benefits and have high expectations. At the same time, the powers of AI have been rising so strongly that it is no longer obvious that AI applications (whether in the law or elsewhere) help promoting a good society; in fact they are sometimes harmful. Hence many argue that safeguards are needed for AI to be trustworthy, social, responsible, humane, ethical. In short: AI should be g…Read more
-
40On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games: 25 years laterArgument and Computation 11 (1-2): 1-14. 2020.
-
22Argument & Computation Community Resources cornerArgument and Computation 10 (2): 105-105. 2019.
-
26Analyzing the Simonshaven Case With and Without ProbabilitiesTopics in Cognitive Science 12 (4): 1175-1199. 2020.This paper is one in a series of rational analyses of the Dutch Simonshaven case, each using a different theoretical perspective. The theoretical perspectives discussed in the literature typically use arguments, scenarios, and probabilities, in various combinations. The theoretical perspective on evidential reasoning used in this paper has been designed to connect arguments, scenarios, and probabilities in a single formal modeling approach, in an attempt to investigate bridges between qualitativ…Read more
-
6Review of The dynamics of judicial proof, computation, logic, and common sense, by M. MacCrimmon and P. Tillers (eds.), Physica-Verlag, Heidelberg, 2002 (review)Artificial Intelligence and Law 11 (4): 299-303. 2003.
-
15Formalizing value-guided argumentation for ethical systems designArtificial Intelligence and Law 24 (4): 387-407. 2016.The persuasiveness of an argument depends on the values promoted and demoted by the position defended. This idea, inspired by Perelman’s work on argumentation, has become a prominent theme in artificial intelligence research on argumentation since the work by Hafner and Berman on teleological reasoning in the law, and was further developed by Bench-Capon in his value-based argumentation frameworks. One theme in the study of value-guided argumentation is the comparison of values. Formal models in…Read more
-
60A method for explaining Bayesian networks for legal evidence with scenariosArtificial Intelligence and Law 24 (3): 285-324. 2016.In a criminal trial, a judge or jury needs to reason about what happened based on the available evidence, often including statistical evidence. While a probabilistic approach is suitable for analysing the statistical evidence, a judge or jury may be more inclined to use a narrative or argumentative approach when considering the case as a whole. In this paper we propose a combination of two approaches, combining Bayesian networks with scenarios. Whereas a Bayesian network is a popular tool for an…Read more
-
41Research in progress: report on the ICAIL 2017 doctoral consortiumArtificial Intelligence and Law 26 (1): 49-97. 2018.This paper arose out of the 2017 international conference on AI and law doctoral consortium. There were five students who presented their Ph.D. work, and each of them has contributed a section to this paper. The paper offers a view of what topics are currently engaging students, and shows the diversity of their interests and influences.
-
Book review: Formalism and interpretation in the logic of law (review)Artificial Intelligence and Law 8 35-65. 2000.
-
123Solving a Murder Case by Asking Critical Questions: An Approach to Fact-Finding in Terms of Argumentation and Story Schemes (review)Argumentation 26 (3): 325-353. 2012.In this paper, we look at reasoning with evidence and facts in criminal cases. We show how this reasoning may be analysed in a dialectical way by means of critical questions that point to typical sources of doubt. We discuss critical questions about the evidential arguments adduced, about the narrative accounts of the facts considered, and about the way in which the arguments and narratives are connected in an analysis. Our treatment shows how two different types of knowledge, represented as sch…Read more
-
4Douglas Walton, The New Dialectic. Conversational Contexts of Argument. Toronto: University of Toronto Press (Book Review) (review)Artificial Intelligence and Law 9 (4): 305-313. 2001.