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  1. A General Structure for Legal Arguments About Evidence Using Bayesian Networks.Norman Fenton, Martin Neil & David A. Lagnado - 2013 - Cognitive Science 37 (1):61-102.
    A Bayesian network (BN) is a graphical model of uncertainty that is especially well suited to legal arguments. It enables us to visualize and model dependencies between different hypotheses and pieces of evidence and to calculate the revised probability beliefs about all uncertain factors when any piece of new evidence is presented. Although BNs have been widely discussed and recently used in the context of legal arguments, there is no systematic, repeatable method for modeling legal arguments as BNs. Hence, where (...)
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  • Pure theory of law.Hans Kelsen - 1967 - Clark, N.J.: Lawbook Exchange.
    I LAW AND NATURE i. The "Pure" Theory The Pure Theory of Law is a theory of positive law. It is a theory of positive law in general, not of a specific legal ...
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  • Modelling competing legal arguments using Bayesian model comparison and averaging.Martin Neil, Norman Fenton, David Lagnado & Richard David Gill - 2019 - Artificial Intelligence and Law 27 (4):403-430.
    Bayesian models of legal arguments generally aim to produce a single integrated model, combining each of the legal arguments under consideration. This combined approach implicitly assumes that variables and their relationships can be represented without any contradiction or misalignment, and in a way that makes sense with respect to the competing argument narratives. This paper describes a novel approach to compare and ‘average’ Bayesian models of legal arguments that have been built independently and with no attempt to make them consistent (...)
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  • Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.J. Pearl, F. Bacchus, P. Spirtes, C. Glymour & R. Scheines - 1988 - Synthese 104 (1):161-176.
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  • MEBN: A language for first-order Bayesian knowledge bases.Kathryn Blackmond Laskey - 2008 - Artificial Intelligence 172 (2-3):140-178.
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  • Probabilistic argumentation.Rolf Haenni - 2009 - Journal of Applied Logic 7 (2):155-176.
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