Steps Towards Programs that Manage Uncertainty

TL;DR

This paper discusses the development of MUM, an expert system designed to manage uncertainty in medical diagnosis by planning diagnostic sequences, and introduces MU, a simplified version for building uncertainty-aware expert systems.

Contribution

It presents the architecture of MUM and MU, highlighting their capabilities in managing uncertainty and planning diagnostic actions in expert systems.

Findings

MUM effectively plans diagnostic sequences under uncertainty.

MU provides a flexible platform for building uncertainty-managing expert systems.

Reimplementation demonstrates MU's suitability for diverse diagnostic domains.

Abstract

Reasoning under uncertainty in Al hats come to mean assessing the credibility of hypotheses inferred from evidence. But techniques for assessing credibility do not tell a problem solver what to do when it is uncertain. This is the focus of our current research. We have developed a medical expert system called MUM, for Managing Uncertainty in Medicine, that plans diagnostic sequences of questions, tests, and treatments. This paper describes the kinds of problems that MUM was designed to solve and gives a brief description of its architecture. More recently, we have built an empty version of MUM called MU, and used it to reimplement MUM and a small diagnostic system for plant pathology. The latter part of the paper describes the features of MU that make it appropriate for building expert systems that manage uncertainty.