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  1.  51
    Argument diagram extraction from evidential Bayesian networks.Jeroen Keppens - 2012 - Artificial Intelligence and Law 20 (2):109-143.
    Bayesian networks (BN) and argumentation diagrams (AD) are two predominant approaches to legal evidential reasoning, that are often treated as alternatives to one another. This paper argues that they are, instead, complimentary and proposes the beginnings of a method to employ them in such a manner. The Bayesian approach tends to be used as a means to analyse the findings of forensic scientists. As such, it constitutes a means to perform evidential reasoning. The design of Bayesian networks that accurately and (...)
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  2.  24
    Establishing norms with metanorms in distributed computational systems.Samhar Mahmoud, Nathan Griffiths, Jeroen Keppens, Adel Taweel, Trevor J. M. Bench-Capon & Michael Luck - 2015 - Artificial Intelligence and Law 23 (4):367-407.
    Norms provide a valuable mechanism for establishing coherent cooperative behaviour in decentralised systems in which there is no central authority. One of the most influential formulations of norm emergence was proposed by Axelrod :1095–1111, 1986). This paper provides an empirical analysis of aspects of Axelrod’s approach, by exploring some of the key assumptions made in previous evaluations of the model. We explore the dynamics of norm emergence and the occurrence of norm collapse when applying the model over extended durations. It (...)
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  3.  27
    A formalisation and prototype implementation of argumentation for statistical model selection.Isabel Sassoon, Sebastian Zillessen, Jeroen Keppens & Peter McBurney - 2018 - Argument and Computation 10 (1):83-103.
  4.  38
    On modelling non-probabilistic uncertainty in the likelihood ratio approach to evidential reasoning.Jeroen Keppens - 2014 - Artificial Intelligence and Law 22 (3):239-290.
    When the likelihood ratio approach is employed for evidential reasoning in law, it is often necessary to employ subjective probabilities, which are probabilities derived from the opinions and judgement of a human. At least three concerns arise from the use of subjective probabilities in legal applications. Firstly, human beliefs concerning probabilities can be vague, ambiguous and inaccurate. Secondly, the impact of this vagueness, ambiguity and inaccuracy on the outcome of a probabilistic analysis is not necessarily fully understood. Thirdly, the provenance (...)
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