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Erschienen in:
2014 | OriginalPaper | Buchkapitel
On Causal Compositional Models: Simple Examples
verfasst von : Radim Jiroušek
Erschienen in: Information Processing and Management of Uncertainty in Knowledge-Based Systems
Verlag: Springer International Publishing
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The “algebraic” form of representation of probabilistic causal systems by compositional models seems to be quite useful and advantageous because of two reasons. First, decomposition of the model into its low-dimensional parts makes some of computations feasible, and, second, it appears that within these models, both conditioning and intervention can be realized as a composition of the model with a degenerated one-dimensional distribution. The syntax of these two computational processes are similar to each other; they differ just by one pair of brackets. Moreover, as it is shown in the last part of this paper on examples, it appears that these models can also cope with the problem of unobserved variables elimination.