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Some graph algorithms for causal network expert systems
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Organization: | University of Cantabria |
Department: | Department of Applied Mathematics and Computational Science |
Organization: | University of Cantabria |
Department: | Department of Applied Mathematics and Computational Science |
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Mathematics with Vision: Proceedings of the First International Mathematica Symposium |
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Recent developments in the graphical representation of discrete joint distribution provide computational algorithms for propagating the effects of new evidence in causal networks. This paper presents some graph algorithms needed to transform an initial graph by grouping complete sets of nodes obtaining secondary related structures. These structures can be applied to causal network expert systems to allow uncertainty propagation to be done in a efficient way.
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