论文信息 - Probabilistic reasoning in evidential assessment

Probabilistic reasoning in evidential assessment

Computational procedures, based on probabilities for incorporating and assessing evidence obtained in the course of a criminal investigation, are described. These procedures depend on a network approach. Suspects and individual pieces of evidence are the nodes of the network. Causal connections are the links of the network. Various applications of the procedures are discussed in the context of one artificial example.

Colin Aitken | Alexander Gammerman

[1] Bruce G. Buchanan,et al. The MYCIN Experiments of the Stanford Heuristic Programming Project , 1985 .

[2] Michael C. Grieve,et al. Transfer experiments with acrylic fibres , 1989 .

[3] Robert E. Tarjan,et al. Simple Linear-Time Algorithms to Test Chordality of Graphs, Test Acyclicity of Hypergraphs, and Selectively Reduce Acyclic Hypergraphs , 1984, SIAM J. Comput..

[4] Ian W. Evett,et al. Evaluation of the likelihood ratio for fibre transfer evidence in criminal cases , 1987 .

[5] David J. Spiegelhalter,et al. Local computations with probabilities on graphical structures and their application to expert systems , 1990 .

[6] John Gaschnig,et al. MODEL DESIGN IN THE PROSPECTOR CONSULTANT SYSTEM FOR MINERAL EXPLORATION , 1981 .

[7] L. N. Kanal,et al. Uncertainty in Artificial Intelligence 5 , 1990 .

[8] David J. Spiegelhalter,et al. Probabilistic Reasoning in Predictive Expert Systems , 1985, UAI.

[9] T. Speed,et al. Recursive causal models , 1984, Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics.