6 found
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  1.  48
    A method for explaining Bayesian networks for legal evidence with scenarios.Charlotte S. Vlek, Henry Prakken, Silja Renooij & Bart Verheij - 2016 - Artificial Intelligence and Law 24 (3):285-324.
    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 analysing (...)
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  2.  45
    Building Bayesian networks for legal evidence with narratives: a case study evaluation.Charlotte S. Vlek, Henry Prakken, Silja Renooij & Bart Verheij - 2014 - Artificial Intelligence and Law 22 (4):375-421.
    In a criminal trial, evidence is used to draw conclusions about what happened concerning a supposed crime. Traditionally, the three main approaches to modeling reasoning with evidence are argumentative, narrative and probabilistic approaches. Integrating these three approaches could arguably enhance the communication between an expert and a judge or jury. In previous work, techniques were proposed to represent narratives in a Bayesian network and to use narratives as a basis for systematizing the construction of a Bayesian network for a legal (...)
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  3.  5
    Context-specific sign-propagation in qualitative probabilistic networks.Silja Renooij, Linda C. van der Gaag & Simon Parsons - 2002 - Artificial Intelligence 140 (1-2):207-230.
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  4.  4
    Enhanced qualitative probabilistic networks for resolving trade-offs.Silja Renooij & Linda C. van der Gaag - 2008 - Artificial Intelligence 172 (12-13):1470-1494.
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  5.  7
    Arguments, rules and cases in law: Resources for aligning learning and reasoning in structured domains.Cor Steging, Silja Renooij, Bart Verheij & Trevor Bench-Capon - 2023 - Argument and Computation 14 (2):235-243.
    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.
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  6.  15
    Deductive and abductive argumentation based on information graphs.Remi Wieten, Floris Bex, Henry Prakken & Silja Renooij - 2022 - Argument and Computation 13 (1):49-91.
    In this paper, we propose an argumentation formalism that allows for both deductive and abductive argumentation, where ‘deduction’ is used as an umbrella term for both defeasible and strict ‘forward’ inference. Our formalism is based on an extended version of our previously proposed information graph formalism, which provides a precise account of the interplay between deductive and abductive inference and causal and evidential information. In the current version, we consider additional types of information such as abstractions which allow domain experts (...)
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