Abstract
After having discussed efficient representations for expert and domain knowledge, we intent to exploit them to draw inferences when new information (evidence) becomes known. Using the Volkswagen example from the last chapter, an inference could be the update of the probabilities of certain car parts combinations when the customer has chosen, say, the engine type to be m ∗. The objective is to propagate the evidence through the underlying network to reach all relevant attributes. Obviously, the graph structure will play an important role.
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Kruse, R., Borgelt, C., Klawonn, F., Moewes, C., Steinbrecher, M., Held, P. (2013). Evidence Propagation. In: Computational Intelligence. Texts in Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-5013-8_24
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DOI: https://doi.org/10.1007/978-1-4471-5013-8_24
Publisher Name: Springer, London
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