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References (23)
-
C Berger, D Aben (2010)
Bewijs en overtuiging: Een helder zicht op valkuilenExpertise en Recht, 5
-
CD Poot, R Bokhorst, P Koppen, E Mulder (2004)
Recherche portret: over dilemma’s in de opsporing -
F Taroni, C Aitken, P Garbolino, A Biedermann (2006)
Bayesian networks and probabilistic inference in forensic science -
J Pearl (1988)
Embracing causality in default reasoningArtif Intel, 35
-
F Jensen, T Nielsen (2007)
Bayesian networks and decision graphs -
H Prakken (2010)
An abstract framework for argumentation with structured argumentsArgum Comput, 1
-
N Fenton, M Neil (2000)
The “jury observation fallacy” and the use of Bayesian networks to present probabilistic legal argumentsMath Today, 36
-
J Keppens, B Schafer (2006)
Knowledge based crime scenario modellingExpert Syst Appl, 30
-
N Fenton, M Neil, D Lagnado (2013)
A general structure for legal arguments using Bayesian networksCognit Sci, 37
-
R Schank, R Abelson (1977)
Scripts, plans, goals and understanding, an inquiry into human knowledge structures -
F Bex (2011)
Arguments, stories and criminal evidence, a formal hybrid theory -
F Bex, P Koppen, H Prakken, B Verheij (2010)
A hybrid formal theory of arguments, stories and criminal evidenceArtif Intel Law, 18
-
T Handfield (2012)
A philosophical guide to chance: physical probability -
S Renooij (2001)
Probability elicitation for belief networks: issues to considerKnowl Eng Rev, 16
-
C Berger, D Aben (2010)
Bewijs en overtuiging: redeneren in de rechtszaalExpert Recht, 3
-
D Rumelhart (1975)
Representation and understanding: studies in cognitive science -
C Berger, D Aben (2010)
Bewijs en overtuiging: rationeel redeneren sinds aristotelesExpert Recht, 2
-
D Lagnado, N Fenton, M Neil (2013)
Legal idioms: a framework for evidential reasoningArgum Comput, 4
-
(2009)
Legal evidence and proof: statistics, stories, logic -
W Wagenaar, P Koppen, H Crombag (1993)
Anchored narratives: the psychology of criminal evidence -
N Pennington, R Hastie (1992)
Explaining the evidence: tests of the story model for juror decision makingJ PersonSoc Psychol, 62
-
J Keppens (2011)
The 13th international conference on artificial intelligence and law -
A Hepler, A Dawid, V Leucari (2004)
Object-oriented graphical representations of complex patterns of evidenceLaw Probab Risk, 6
- Publisher
- Springer Journals
- Copyright
- Copyright © 2014 by Springer Science+Business Media Dordrecht
- Subject
- Computer Science; Artificial Intelligence (incl. Robotics); International IT and Media Law, Intellectual Property Law; Philosophy of Law; Legal Aspects of Computing; Information Storage and Retrieval
- ISSN
- 0924-8463
- eISSN
- 1572-8382
- DOI
- 10.1007/s10506-014-9161-7
- Publisher site
- See Article on Publisher Site
Abstract
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 case. In this paper, these techniques are combined to form a design method for constructing a Bayesian network based on narratives. This design method is evaluated by means of an extensive case study concerning the notorious Dutch case of the Anjum murders.
Journal
Artificial Intelligence and Law – Springer Journals
Published: Aug 9, 2014