Abstract
A metric of causal power can assist in developing and using causal Bayesian networks. We introduce a metric based upon information theory. We show that it generalizes prior metrics restricted to linear and noisy-or models, while providing a metric appropriate to the full representational power of Bayesian nets.
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Hope, L.R., Korb, K.B. (2005). An Information-Theoretic Causal Power Theory. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_85
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DOI: https://doi.org/10.1007/11589990_85
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30462-3
Online ISBN: 978-3-540-31652-7
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