Abstract
This paper presents an architecture for exact evaluation of influence diagrams containing a mixture of continuous and discrete variables. The proposed architecture is the first architecture for efficient exact solution of linear-quadratic conditional Gaussian influence diagrams with an additively decomposing utility function. The solution method as presented in this paper is based on the idea of lazy evaluation. The computational aspects of the architecture are illustrated by example.
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Madsen, A.L., Jensen, F. (2003). Mixed Influence Diagrams. In: Nielsen, T.D., Zhang, N.L. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2003. Lecture Notes in Computer Science(), vol 2711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45062-7_17
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DOI: https://doi.org/10.1007/978-3-540-45062-7_17
Publisher Name: Springer, Berlin, Heidelberg
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