Tag Archives: Modeling evidentiary reasoning

Keppens: On modelling non-probabilistic uncertainty in the likelihood ratio approach to evidential reasoning

Dr. Jeroen Keppens of King’s College London has published On modelling non-probabilistic uncertainty in the likelihood ratio approach to evidential reasoning, forthcoming in Artificial Intelligence and Law. Here is the abstract: When the likelihood ratio approach is employed for evidential … Continue reading

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Call for Papers: Special Issue of Artificial Intelligence and Law: Computational Methods for Enforcing Privacy and Fairness

Dr. Anne Gardner of IAAIL informs us of the following call: CALL FOR PAPERS Special issue of Artificial Intelligence and Law Computational Methods for Enforcing Privacy and Fairness in the Knowledge Society Full Call for Papers: http://enforce.di.unipi.it/specialissue.pdf We invite contributions … 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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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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