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  1. A model of legal reasoning with cases incorporating theories and values.Trevor Bench-Capon & Giovanni Sartor - 2003 - Artificial Intelligence 150 (1-2):97-143.
    Reasoning with cases has been a primary focus of those working in AI and law who have attempted to model legal reasoning. In this paper we put forward a formal model of reasoning with cases which captures many of the insights from that previous work. We begin by stating our view of reasoning with cases as a process of constructing, evaluating and applying a theory. Central to our model is a view of the relationship between cases, rules based on cases, (...)
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  • HYPO's legacy: introduction to the virtual special issue.T. J. M. Bench-Capon - 2017 - Artificial Intelligence and Law 25 (2):205-250.
    This paper is an introduction to a virtual special issue of AI and Law exploring the legacy of the influential HYPO system of Rissland and Ashley. The papers included are: Arguments and cases: An inevitable intertwining, BankXX: Supporting legal arguments through heuristic retrieval, Modelling reasoning with precedents in a formal dialogue Game, A note on dimensions and factors, An empirical investigation of reasoning with legal cases through theory construction and application, Automatically classifying case texts and predicting outcomes, A factor-based definition (...)
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  • Reasoning with dimensions and magnitudes.John Horty - 2019 - Artificial Intelligence and Law 27 (3):309-345.
    This paper shows how two models of precedential constraint can be broadened to include legal information represented through dimensions. I begin by describing a standard representation of legal cases based on boolean factors alone, and then reviewing two models of constraint developed within this standard setting. The first is the “result model”, supporting only a fortiori reasoning. The second is the “reason model”, supporting a richer notion of constraint, since it allows the reasons behind a court’s decisions to be taken (...)
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  • Representing dimensions within the reason model of precedent.Adam Rigoni - 2018 - Artificial Intelligence and Law 26 (1):1-22.
    This paper gives an account of dimensions in the reason model found in Horty : 1–33, 2011), Horty and Bench-Capon and Rigoni :133–160, 2015. doi: 10.1007/s10506-015-9166-x). The account is constructed with the purpose of rectifying problems with the approach to incorporating dimensions in Horty, namely, the problems arising from the collapse of the distinction between the reason model and the result model on that approach. Examination of the newly constructed theory revealed that the importance of dimensions in the reason model (...)
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  • Law and logic: A review from an argumentation perspective.Henry Prakken & Giovanni Sartor - 2015 - Artificial Intelligence 227 (C):214-245.
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  • Thirty years of Artificial Intelligence and Law: the second decade.Giovanni Sartor, Michał Araszkiewicz, Katie Atkinson, Floris Bex, Tom van Engers, Enrico Francesconi, Henry Prakken, Giovanni Sileno, Frank Schilder, Adam Wyner & Trevor Bench-Capon - 2022 - Artificial Intelligence and Law 30 (4):521-557.
    The first issue of Artificial Intelligence and Law journal was published in 1992. This paper provides commentaries on nine significant papers drawn from the Journal’s second decade. Four of the papers relate to reasoning with legal cases, introducing contextual considerations, predicting outcomes on the basis of natural language descriptions of the cases, comparing different ways of representing cases, and formalising precedential reasoning. One introduces a method of analysing arguments that was to become very widely used in AI and Law, namely (...)
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  • An exercise in formalising teleological case-based reasoning.Henry Prakken - 2002 - Artificial Intelligence and Law 10 (1-3):113-133.
    This paper takes up Berman and Hafner's (1993) challenge to model legal case-based reasoning not just in terms of factual similarities and differences but also in terms of the values that are at stake. The formal framework of Prakken and Sartor (1998) is applied to examples of case-based reasoning involving values, and a method for formalising such examples is proposed. The method makes it possible to express that a case should be decided in a certain way because that advances certain (...)
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  • Representing Popov v Hayashi with dimensions and factors.T. J. M. Bench-Capon - 2012 - Artificial Intelligence and Law 20 (1):15-35.
    Modelling reasoning with legal cases has been a central concern of AI and Law since the 1980s. The approach which represents cases as factors and dimensions has been a central part of that work. In this paper I consider how several varieties of the approach can be applied to the interesting case of Popov v Hayashi. After briefly reviewing some of the key landmarks of the approach, the case is represented in terms of factors and dimensions, and further explored using (...)
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  • Two factor-based models of precedential constraint: a comparison and proposal.Robert Mullins - 2023 - Artificial Intelligence and Law 31 (4):703-738.
    The article considers two different interpretations of the reason model of precedent pioneered by John Horty. On a plausible interpretation of the reason model, past cases provide reasons to prioritize reasons favouring the same outcome as a past case over reasons favouring the opposing outcome. Here I consider the merits of this approach to the role of precedent in legal reasoning in comparison with a closely related view favoured by some legal theorists, according to which past cases provide reasons for (...)
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  • Teleological arguments and theory-based dialectics.Giovanni Sartor - 2002 - Artificial Intelligence and Law 10 (1-3):95-112.
    This paper proposes to model legal reasoning asdialectical theory-constructiondirected by teleology. Precedents are viewed asevidence to be explained throughtheories. So, given a background of factors andvalues, the parties in a case canbuild their theories by using a set of operators,which are called theory constructors.The objective of each party is to provide theoriesthat both explain the evidence (theprecedents) and support the decision wished by thatparty. This leads to theory-basedargumentation, i.e., a dialectical exchange ofcompeting theories, which support opposedoutcomes by explaining the same (...)
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  • Legal case-based reasoning as practical reasoning.Katie Atkinson & Trevor Bench-Capon - 2005 - Artificial Intelligence and Law 13 (1):93-131.
    In this paper we apply a general account of practical reasoning to arguing about legal cases. In particular, we provide a reconstruction of the reasoning of the majority and dissenting opinions for a particular well-known case from property law. This is done through the use of Belief-Desire-Intention (BDI) agents to replicate the contrasting views involved in the actual decision. This reconstruction suggests that the reasoning involved can be separated into three distinct levels: factual and normative levels and a level connecting (...)
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  • Accommodating change.Latifa Al-Abdulkarim, Katie Atkinson & Trevor Bench-Capon - 2016 - Artificial Intelligence and Law 24 (4):409-427.
    The third of Berman and Hafner’s early nineties papers on reasoning with legal cases concerned temporal context, in particular the evolution of case law doctrine over time in response to new cases and against a changing background of social values and purposes. In this paper we consider the ways in which changes in case law doctrine can be accommodated in a recently proposed methodology for encapsulating case law theories, and relate these changes the sources of change identified by Berman and (...)
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  • Before and after Dung: Argumentation in AI and Law.T. J. M. Bench-Capon - 2020 - Argument and Computation 11 (1-2):221-238.
    Dung’s abstract argumentation frameworks have had a very significant role in the rise in interest in argumentation throughout this century. In this paper we will explore the impact of this seminal idea on a specific application domain, AI and Law. Argumentation is central to legal reasoning and there had been a considerable amount of work on it in AI and Law before Dung’s paper. It had, however, been rather fragmented. We argue that the abstract argumentation frameworks had a unifying effect (...)
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  • An empirical investigation of reasoning with legal cases through theory construction and application.Alison Chorley & Trevor Bench-Capon - 2005 - Artificial Intelligence and Law 13 (3-4):323-371.
    In recent years several proposals to view reasoning with legal cases as theory construction have been advanced. The most detailed of these is that of Bench-Capon and Sartor, which uses facts, rules, values and preferences to build a theory designed to explain the decisions in a set of cases. In this paper we describe CATE (CAse Theory Editor), a tool intended to support the construction of theories as described by Bench-Capon and Sartor, and which produces executable code corresponding to a (...)
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  • Resources for Research on Analogy: A Multi-disciplinary Guide.Marcello Guarini, Amy Butchart, Paul Simard Smith & Andrei Moldovan - 2009 - Informal Logic 29 (2):84-197.
    Work on analogy has been done from a number of disciplinary perspectives throughout the history of Western thought. This work is a multidisciplinary guide to theorizing about analogy. It contains 1,406 references, primarily to journal articles and monographs, and primarily to English language material. classical through to contemporary sources are included. The work is classified into eight different sections (with a number of subsections). A brief introduction to each section is provided. Keywords and key expressions of importance to research on (...)
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  • Before and after Dung: Argumentation in AI and Law.Francesca Toni - 2020 - Argument and Computation 11 (1-2):221-238.
    Dung’s abstract argumentation frameworks have had a very significant role in the rise in interest in argumentation throughout this century. In this paper we will explore the impact of this seminal idea on a specific application domain, AI and Law. Argumentation is central to legal reasoning and there had been a considerable amount of work on it in AI and Law before Dung’s paper. It had, however, been rather fragmented. We argue that the abstract argumentation frameworks had a unifying effect (...)
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  • A legal case OWL ontology with an instantiation of Popov v. Hayashi.Adam Wyner & Rinke Hoekstra - 2012 - Artificial Intelligence and Law 20 (1):83-107.
    The paper provides an OWL ontology for legal cases with an instantiation of the legal case Popov v. Hayashi. The ontology makes explicit the conceptual knowledge of the legal case domain, supports reasoning about the domain, and can be used to annotate the text of cases, which in turn can be used to populate the ontology. A populated ontology is a case base which can be used for information retrieval, information extraction, and case based reasoning. The ontology contains not only (...)
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  • Comparing alternatives in the law.Jaap Hage - 2004 - Artificial Intelligence and Law 12 (3):181-225.
    This paper argues the thesis that a particular style of reasoning, qualitative comparative reasoning (QCR), plays a role in at least three areas of legal reasoning that are central in AI and law research, namely legal theory construction, case-based reasoning in the form of case comparison, and legal proof. The paper gives an informal exposition of one particular way to deal with QCR, based on the author’s previous work on reason-based logic (RBL). Then it contains a substantially adapted formalisation of (...)
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  • On argument acceptability change towards legal interpretation dynamics.Martín O. Moguillansky & Luciano H. Tamargo - 2020 - Artificial Intelligence and Law 29 (3):311-350.
    We propose a formal theory built upon an abstract argumentation framework for handling argumentation dynamics. To that end, we analyze the acceptability dynamics of arguments through the proposal of two different kinds of sets of arguments which are somehow responsible for the acceptability/rejection of a given argument. We develop a study of the consequences of breaking the construction of such sets towards the acceptance of an analyzed argument. This brings about the proposal of a novel change operation which allows to (...)
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  • How to justify a backing’s eligibility for a warrant: the justification of a legal interpretation in a hard case.Shiyang Yu & Xi Chen - 2023 - Artificial Intelligence and Law 31 (2):239-268.
    The Toulmin model has been proved useful in law and argumentation theory. This model describes the basic process in justifying a claim, which comprises six elements, i.e., claim (C), data (D), warrant (W), backing (B), qualifier (Q), and rebuttal (R). Specifically, in justifying a claim, one must put forward ‘data’ and a ‘warrant’, whereas the latter is authorized by ‘backing’. The force of the ‘claim’ being justified is represented by the ‘qualifier’, and the condition under which the claim cannot be (...)
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  • A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law. [REVIEW]Trevor Bench-Capon, Michał Araszkiewicz, Kevin Ashley, Katie Atkinson, Floris Bex, Filipe Borges, Daniele Bourcier, Paul Bourgine, Jack G. Conrad, Enrico Francesconi, Thomas F. Gordon, Guido Governatori, Jochen L. Leidner, David D. Lewis, Ronald P. Loui, L. Thorne McCarty, Henry Prakken, Frank Schilder, Erich Schweighofer, Paul Thompson, Alex Tyrrell, Bart Verheij, Douglas N. Walton & Adam Z. Wyner - 2012 - Artificial Intelligence and Law 20 (3):215-319.
    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 (...)
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  • From Berman and Hafner’s teleological context to Baude and Sachs’ interpretive defaults: an ontological challenge for the next decades of AI and Law.Ronald P. Loui - 2016 - Artificial Intelligence and Law 24 (4):371-385.
    This paper revisits the challenge of Berman and Hafner’s “missing link” paper on representing teleological structure in case-based legal reasoning. It is noted that this was mainly an ontological challenge to represent some of what made legal reasoning distinctive, which was given less attention than factual similarity in the dominant AI and Law paradigm, deriving from HYPO. The response to their paper is noted and briefly evaluated. A parallel is drawn to a new challenge to provide deep structure to the (...)
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  • Argumentation in AI and law: Editors' introduction. [REVIEW]Trevor J. M. Bench-Capon & Paul E. Dunne - 2005 - Artificial Intelligence and Law 13 (1):1-8.
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