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Analysing reasoning about evidence with formal models of argumentation

Analysing reasoning about evidence with formal models of argumentation Abstract This paper is on the formal modelling of reasoning about evidence. The main purpose is to advocate logical approaches as a worthwhile alternative to approaches rooted in probability theory. In particular, the use of logics for defeasible argumentation is investigated. Such logics model reasoning as the construction and comparison of arguments for and against a conclusion; this makes them very suitable for capturing the adversarial aspects that are so typical for legal evidential reasoning. Also, it will be shown that they facilitate the explicit modelling of different kinds of knowledge, such as the distinction between direct vs. ancillary evidence, and the explicit modelling of different types of evidential arguments, such as appeals to witness or expert opinion, applying generalizations, or temporal projections. Received 6 June 2003. Revised 24 December 2003. Author notes 1Institute of Information and Computing Sciences, Utrecht University, PO Box 80 089, 3508 TB Utrecht, The Netherlands Copyright Oxford University Press 2004 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Law, Probability and Risk Oxford University Press

Analysing reasoning about evidence with formal models of argumentation

Law, Probability and Risk , Volume 3 (1) – Mar 1, 2004

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References (30)

Publisher
Oxford University Press
Copyright
Copyright Oxford University Press 2004
ISSN
1470-8396
eISSN
1470-840X
DOI
10.1093/lpr/3.1.33
Publisher site
See Article on Publisher Site

Abstract

Abstract This paper is on the formal modelling of reasoning about evidence. The main purpose is to advocate logical approaches as a worthwhile alternative to approaches rooted in probability theory. In particular, the use of logics for defeasible argumentation is investigated. Such logics model reasoning as the construction and comparison of arguments for and against a conclusion; this makes them very suitable for capturing the adversarial aspects that are so typical for legal evidential reasoning. Also, it will be shown that they facilitate the explicit modelling of different kinds of knowledge, such as the distinction between direct vs. ancillary evidence, and the explicit modelling of different types of evidential arguments, such as appeals to witness or expert opinion, applying generalizations, or temporal projections. Received 6 June 2003. Revised 24 December 2003. Author notes 1Institute of Information and Computing Sciences, Utrecht University, PO Box 80 089, 3508 TB Utrecht, The Netherlands Copyright Oxford University Press 2004

Journal

Law, Probability and RiskOxford University Press

Published: Mar 1, 2004

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