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Artificial Intelligence and Law

, Volume 22, Issue 4, pp 375–421 | Cite as

Building Bayesian networks for legal evidence with narratives: a case study evaluation

  • Charlotte S. Vlek
  • Henry Prakken
  • Silja Renooij
  • Bart Verheij
Article

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.

Keywords

Legal reasoning Bayesian networks Narrative 

Notes

Acknowledgments

This work is part of the project “Designing and Understanding Forensic Bayesian Networks with Arguments and Scenarios” in the Forensic Science programme, financed by the Netherlands Organisation for Scientific Research (NWO). More information about the project: www.ai.rug.nl/~verheij/nwofs

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Charlotte S. Vlek
    • 1
  • Henry Prakken
    • 2
    • 3
  • Silja Renooij
    • 2
  • Bart Verheij
    • 1
    • 4
  1. 1.Institute of Artificial IntelligenceUniversity of GroningenGroningenThe Netherlands
  2. 2.Department of Information and Computing SciencesUtrecht UniversityUtrechtThe Netherlands
  3. 3.Faculty of LawUniversity of GroningenGroningenThe Netherlands
  4. 4.CodeXStanford UniversityStanfordUSA

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