An information-theoretic causal power theory

  • Authors:
  • Lucas R. Hope;Kevin B. Korb

  • Affiliations:
  • School of Information Technology, Monash University, Clayton, Victoria, Australia;School of Information Technology, Monash University, Clayton, Victoria, Australia

  • Venue:
  • AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
  • Year:
  • 2005

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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.