Probabilistic abductive computation of evidence collection strategies in crime investigation


Autoria(s): Keppens, Jeroen; Schafer, Burkhard; Shen, Qiang
Contribuinte(s)

Department of Computer Science

Advanced Reasoning Group

Data(s)

23/01/2008

23/01/2008

2005

Resumo

J. Keppens, Q. Shen and B. Schafer. Probabilistic abductive computation of evidence collection strategies in crime investigation. Proceedings of the 10th International Conference on Artificial Intelligence and Law, pages 215-225.

This paper presents a methodology for integrating two approaches to building decision support systems (DSS) for crime investigation: symbolic crime scenario abduction [16] and Bayesian forensic evidence evaluation [5]. This is achieved by means of a novel compositional modelling technique that allows for automatically generating a space of models describing plausible crime scenarios from given evidence and formally represented domain knowledge. The main benefit of this integration is that the resulting DSS is capable to formulate effective evidence collection strategies useful for differentiating competing crime scenarios. A running example is used to demonstrate the theoretical developments.

Non peer reviewed

Formato

11

Identificador

Keppens , J , Schafer , B & Shen , Q 2005 , ' Probabilistic abductive computation of evidence collection strategies in crime investigation ' pp. 215-225 .

PURE: 74569

PURE UUID: 543ae7aa-b7a3-4684-b404-1ff52a1f06f4

dspace: 2160/463

http://hdl.handle.net/2160/463

Idioma(s)

eng

Tipo

/dk/atira/pure/researchoutput/researchoutputtypes/contributiontoconference/paper

Conference paper

Relação

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