Causal Model with Uncertain Time-series Events for Reasoning Causes

Abstract

Probability and possibility are both convenient scales of uncertainty, because they are defined by a distribution function. They also have complementary properties in the sense that probability is a quantitative and objective ratio scale, while possibility is a qualitative and subjective ordinal scale. The paper discusses probabilistic and possibilistic causal models with time-series events from the viewpoint of Evidence theory, and shows that they can be defined by a single equation with different conditions of focal elements using the basic probability assignments.