The paper addresses uncertain reasoning based on causal knowledge given by two layered networks, where nodes in one layer express possible causes and those in the other are possible effects. Uncertainties of the causalities are given by conditional causal possibilities, which were proposed to express the exact degrees of possibility of causalities. They also have an advantage over the conventional conditional possibilities in the number of possibilistic values that should be given as a priori knowledge. The number of conditional causal possibilities given as knowledge is far smaller than that of conventional conditional possibilities. However, their weakness is that they cannot deal with causalities with compound effects by plural causes, such as synergistic and canceling effects on uncertainty of causalities. The paper discusses this weakness and proposes a solution
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