Efficient Minimum Information Updating for Bayesian Inferencing in Expert Systems
Abstract
This short paper Dresents a new algorithm for minimun information Inferencing within Expert Systems. This algorithm is as efficient in both time and space as previously reported work [3 3 but always provides a minimum information result. In addition to describing the new algorithm, we will prove that it does indeed satisfy minimum information criteria. Since both algorithms are sub stantially different from the Bayesian approaches in well known expert systems such as the original Prospector [1], AL/X [8], and MYCIN [9 3, and from the approach of Kulikowski [5], background is provided to show the motivation for using the minimum information approach to updating.
Cite
Text
Lemmer and Barth. "Efficient Minimum Information Updating for Bayesian Inferencing in Expert Systems." AAAI Conference on Artificial Intelligence, 1982.Markdown
[Lemmer and Barth. "Efficient Minimum Information Updating for Bayesian Inferencing in Expert Systems." AAAI Conference on Artificial Intelligence, 1982.](https://mlanthology.org/aaai/1982/lemmer1982aaai-efficient/)BibTeX
@inproceedings{lemmer1982aaai-efficient,
title = {{Efficient Minimum Information Updating for Bayesian Inferencing in Expert Systems}},
author = {Lemmer, John F. and Barth, Stephen W.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {1982},
pages = {424-427},
url = {https://mlanthology.org/aaai/1982/lemmer1982aaai-efficient/}
}