Tag Archives: Modeling legal evidentiary reasoning

Vlek et al.: Building Bayesian networks for legal evidence with narratives: A case study evaluation

Charlotte S. Vlek, Henry Prakken, Silja Renooij, and Bart Verheij, have published Building Bayesian networks for legal evidence with narratives: a case study evaluation, forthcoming in Artificial Intelligence and Law. Here is the abstract: In a criminal trial, evidence is … Continue reading

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Fenton et al.: Calculating the value of match evidence when there are potential testing errors

Professor Dr. Norman Fenton, Professor Dr. Martin Neil, and Dr. Anne Hsu, all of Queen Mary University of London, have published Calculating and understanding the value of any type of match evidence when there are potential testing errors, forthcoming in … Continue reading

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Lagnado, Fenton, and Neil: Legal idioms: A framework for evidential reasoning

Dr. David A. Lagnado of University College London, and Professor Dr. Norman Fenton and Professor Dr. Martin Neil, both of Queen Mary University of London, have published Legal idioms: A framework for evidential reasoning, Argument & Computation 4(1), 46-63 (2013). … Continue reading

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Call for Papers: Special issue of AI & Law on Computational Methods for Enforcing Privacy and Fairness

Dr. Thomas F. Gordon of Fraunhofer Institute for Open Communications Systems (FOKUS) tells us that a call for papers has been issued for a special issue of the journal Artificial Intelligence and Law on the topic, “Computational Methods for Enforcing … Continue reading

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Call for Papers: ICAIL 2013: International Conference on Artificial Intelligence and Law

A call for papers — with paper submission deadline of 18 January 2013 — has been issued for ICAIL 2013: 14th International Conference on Artificial Intelligence and Law, to be held 10-14 June 2013 in Rome, Italy. The Twitter account … Continue reading

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Keppens on Argument Diagram Extraction from Evidential Bayesian Networks

Dr. Jeroen Keppens of the King’s College London Department of Informatics has published Argument diagram extraction from evidential Bayesian networks, Artificial Intelligence and Law, 20, 109-143. Here is the abstract: Bayesian networks (BN) and argumentation diagrams (AD) are two predominant … Continue reading

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Bex and Walton: Burdens and Standards of Proof for Inference to the Best Explanation: Three Case Studies

Dr. Floris J. Bex of The University of Dundee Argumentation Research Group, and Professor Dr. Douglas Walton of the University of Windsor Centre for Research in Reasoning, Argumentation and Rhetoric, have published Burdens and standards of proof for inference to … Continue reading

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