Implementing Probabilistic Reasoning

TL;DR

This paper discusses the challenges and benefits of implementing probabilistic reasoning in databases and expert systems, focusing on uncertain data handling and inference methods.

Contribution

It introduces methods for incorporating probabilistic reasoning into expert systems and analyzes practical difficulties and advantages of uncertain data management.

Findings

Probabilistic reasoning enhances expert system capabilities.

Handling uncertain data presents specific practical challenges.

Probabilistic resolution offers potential advantages in inference.

Abstract

General problems in analyzing information in a probabilistic database are considered. The practical difficulties (and occasional advantages) of storing uncertain data, of using it conventional forward- or backward-chaining inference engines, and of working with a probabilistic version of resolution are discussed. The background for this paper is the incorporation of uncertain reasoning facilities in MRS, a general-purpose expert system building tool.