David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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Artificial Intelligence and Law 18 (2):123-152 (2010)
This paper presents a theory of reasoning with evidence in order to determine the facts in a criminal case. The focus is on the process of proof, in which the facts of the case are determined, rather than on related legal issues, such as the admissibility of evidence. In the literature, two approaches to reasoning with evidence can be distinguished, one argument-based and one story-based. In an argument-based approach to reasoning with evidence, the reasons for and against the occurrence of an event, e.g., based on witness testimony, are central. In a story-based approach, evidence is evaluated and interpreted from the perspective of the factual stories as they may have occurred in a case, e.g., as they are defended by the prosecution. In this paper, we argue that both arguments and narratives are relevant and useful in the reasoning with and interpretation of evidence. Therefore, a hybrid approach is proposed and formally developed, doing justice to both the argument-based and the narrative-based perspective. By the formalization of the theory and the associated graphical representations, our proposal is the basis for the design of software developed as a tool to make sense of the evidence in complex cases.
|Keywords||Argumentation Stories Legal evidence|
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References found in this work BETA
Douglas Walton, Chris Reed & Fabrizio Macagno (2008). Argumentation Schemes. Cambridge University Press.
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John L. Pollock (1995). Cognitive Carpentry. MIT Press.
Henry Prakken (2011). An Abstract Framework for Argumentation with Structured Arguments. Argument and Computation 1 (2):93-124.
Douglas Walton (2002). Legal Argumentation and Evidence. Penn State University Press.
Citations of this work BETA
Norman Fenton, Martin Neil & David A. Lagnado (2013). A General Structure for Legal Arguments About Evidence Using Bayesian Networks. Cognitive Science 37 (1):61-102.
Floris Bex & Bart Verheij (2012). Solving 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.
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). A 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.
Jeroen Keppens (2012). Argument Diagram Extraction From Evidential Bayesian Networks. Artificial Intelligence and Law 20 (2):109-143.
Vern R. Walker, Nathaniel Carie, Courtney C. DeWitt & Eric Lesh (2011). A Framework for the Extraction and Modeling of Fact-Finding Reasoning From Legal Decisions: Lessons From the Vaccine/Injury Project Corpus. [REVIEW] Artificial Intelligence and Law 19 (4):291-331.
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