As a member of the Intelligent Systems group at Utrecht University I am working on an NWO Forensic science project. The goal of this project is to combine Bayesian reasoning with Argumentation. The intended application domain of this research is legal reasoning.

Argumentation

The field of AI that deals with formal models of argumentation. Until now uncertainty was modelled by means of defeasible inference rules; rules that can be defeated.

Bayesian networks

This is an often used model to represent uncertain information. Concerned with conditional probabilities and (in)dependence, it is often the tool most suitable for forensic experts to express their findings.

Legal reasoning

With a high degree of formalisation of rules and reasoning, this is the ideal domain for first applications.

[10] S.T. Timmer, J.-J. Meyer, H. Prakken, S.Renooij & B. Verheij. A two-phase method for extracting explanatory arguments from Bayesian networks. International Journal of Approximate Reasoning in press. Elsevier, 2016. [ pdf | bib ]

[9] S. T. Timmer, J.-J. C. Meyer, H. Prakken, S. Renooij, & B. Verheij. Explaining legal Bayesian networks using support graphs. In Legal Knowledge and Information Systems. JURIX 2015: The Twenty-eighth Annual Conference, 2015. [ pdf | bib ]

[8] S. T. Timmer, J.-J. C. Meyer, H. Prakken, S. Renooij, & B. Verheij. Capturing critical questions in Bayesian network fragments. In Legal Knowledge and Information Systems. JURIX 2015: The Twenty-eighth Annual Conference, 2015. [ pdf | bib ]

[7] B. Verheij, F.J. Bex, S.T. Timmer, C.S. Vlek, J.-J. Meyer, S. Renooij & H. Prakken. Arguments, scenarios and probabilities: connections between three normative frameworks for evidential reasoning. Law, Probability & Risk 15(1), 35-70. Oxford Journals, 2016. [ pdf | bib ]

[6] S. T. Timmer, J.-J. C. Meyer, H. Prakken, S. Renooij, & B. Verheij. Explaining Bayesian networks using argumentation. In Symbolic and Quantitative Approaches to Reasoning with Uncertainty - 13th European Conference, ECSQARU 2015, Compiègne, France, July 15-17, 2015. Proceedings, Lecture Notes in Artificial Intelligence. Springer, 2015. [ pdf | bib ]

[5] S. T. Timmer, J.-J. C. Meyer, H. Prakken, S. Renooij, & B. Verheij. A structure-guided approach to capturing Bayesian reasoning about legal evidence in argumentation. In Proceedings of the 15th International Conference on AI and Law, 2015. [ pdf | bib ]

[4] S. T. Timmer, J.-J. C. Meyer, H. Prakken, S. Renooij, & B. Verheij. Demonstration of a structure- guided approach to capturing Bayesian reasoning about legal evidence in argumentation. In Proceedings of the 15th International Conference on AI and Law, 2015. [ pdf | bib ]

[3] H. L. Bodlaender, D. Kratsch, & S. T. Timmer. Exact algorithms for kayles. Theoretical Computer Science, 562:165–176, 2015. [ pdf | bib ]

[2] S. T. Timmer, J.-J. C. Meyer, H. Prakken, S. Renooij, & B. Verheij. Extracting legal arguments from forensic Bayesian networks. In R. Hoekstra, editor, Legal Knowledge and Information Systems. JURIX 2014: The Twenty-seventh Annual Conference, volume 217, pages 71–80, 2014. [ pdf | bib ]

[1] S. T. Timmer, J.-J. C. Meyer, H. Prakken, S. Renooij, & B. Verheij. Inference and attack in Bayesian networks. In K. Hindriks, M. de Weerdt, B. van Riemsdijk, and M. Warnier, editors, Proceedings of the 25th Benelux Conference on Artificial Intelligence, pages 199–206, 2013. [ pdf | bib ]

Visiting address:

Buys Ballotgebouw
Princetonplein 5
Room 519
3584 CC Utrecht
The Netherlands

Get in touch:

s.t.timmer@uu.nl
+31 30 253 4432

Mail address:

Postbus 80.089
3508 TB UTRECHT
The Netherlands