Causal reasoning under uncertainty with Q/C-E networks: A case study on preventive diagnosis of power transformers

P. Baroni, G. Guida, S. Mussi

Proc. AIENG 95 10th Int. Conf. on Applications of Artificial Intelligence in Engineering, Udine, I, 1995, 119-128



The paper presents the formalism of quantified causal-evidential networks (Q/C-E networks) for causal reasoning under uncertainty in networks of propositions. First, the basic concept of C-E network is introduced. The issue of representing uncertainty about propositions and causal-evidential relations is then discussed and Q/C-E networks are defined. Methods for propagating and aggregating uncertainty in a Q/C-E network are proposed and their main properties are illustrated. The proposed approach has been successfully experimented in the design and development of ASTRA, a knowledge-based system for preventive diagnosis of power transformers.

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