Reasoning for causality analysis with possibility and intensity of occurrence

Causality, uncertainty and intensity of occurrence are three important factors we must take into consideration, when we analyze complex problems in the world. Causality is described as “an essential element of human understanding of all phenomena in the world”, and has been used as important knowledge to analyze many real world problems. Uncertainty and intensity of occurrence, on the other hand, are regarded as origins of complexity in analyzing problems. The paper addresses a general causal reasoning with uncertainty and intensity. The paper first defines conditional causal possibility that expresses exact uncertainty of causality, and proposes causality analysis reasoning (CAR) based on possibility theory. CAR is a way of reasoning with a hierarchical causal network, and calculates possibilities of arbitrarily chosen unknown events when some events in the network are observed. Then, it additionally introduces intensity of occurrence to the possibilistic CAR