Incidence Calculus: A Mechanism for Probabilistic Reasoning
This addresses the need for probabilistic reasoning mechanisms in expert systems, offering a novel approach to handle uncertainty with logical properties.
The paper tackles the problem of automating probabilistic reasoning in expert systems by proposing Incidence Calculus, a mechanism that uses sets of points to represent uncertainty and enables truth-functional connectives in probabilistic logic, unlike purely numeric methods.
Mechanisms for the automation of uncertainty are required for expert systems. Sometimes these mechanisms need to obey the properties of probabilistic reasoning. A purely numeric mechanism, like those proposed so far, cannot provide a probabilistic logic with truth functional connectives. We propose an alternative mechanism, Incidence Calculus, which is based on a representation of uncertainty using sets of points, which might represent situations, models or possible worlds. Incidence Calculus does provide a probabilistic logic with truth functional connectives.