Abstract
The forensic scientist often faces the task of interpreting patterns of evidence which involve many variables. Combining different items of evidence within a complex framework of circumstances requires logical powers of reasoning and this can be assisted by formal methods. We discuss one such method which, as has already been pointed out by Aitken and Gammerman (1), offers considerable potential for creating probabilistic expert systems to assist in evidence interpretation. In particular, we show how the method, which is based on a directed acyclic graph, enables dependencies between different aspects of the evidence to be considered. The discussion is based on an imaginary case example.
Issue Section:
Research Papers
Keywords:
forensic science,
interpretation,
expert systems,
probability,
Bayesian,
fibers,
trace evidence
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