Information fractals in evidential reasoning

Evidential reasoning based on a fractal model of belief is outlined. The specific focus is on the fractal modeling of belief functions. After a qualitative justification and interpretation of this model, several concepts and tools needed for its incorporation into evidential reasoning are formally defined. A particularly important concept is that of conductivity, as it provides the basis of partial evidential matching in the present approach to reasoning by analogy. A conductivity analysis algorithm is derived, and it is illustrated by an application to a simple object classification problem. The fractal model provides potentially powerful mechanisms for a quantitative measure of relevance of a piece of evidence to a knowledge base, and a systematic approach to the coarsening and refining of frames of discernment. The proposed model is motivated by applications to the design of intelligent systems, such as sensor-based dexterous manipulators that must operate in unstructured environments in the presence of high levels of uncertainty