Probabilistic Reasoning in Predictive Expert Systems
Abstract
Techniques in developing a coherent probabilistic reasoning system are illustrated with reference to a simplified example. Recent work relating statistical models to graphical representation of causal and associative relationships allows a straightforward means of propagating evidence whilst retaining a probabilistic interpretation for predictive statements. This interpretation allows continual criticism of a system's performance, while imprecise quantitative assessments permit learning from experience. Possible limitations of a formal probabilistic approach are discussed.
Cite
Text
Spiegelhalter. "Probabilistic Reasoning in Predictive Expert Systems." Conference on Uncertainty in Artificial Intelligence, 1985. doi:10.1016/B978-0-444-70058-2.50009-7Markdown
[Spiegelhalter. "Probabilistic Reasoning in Predictive Expert Systems." Conference on Uncertainty in Artificial Intelligence, 1985.](https://mlanthology.org/uai/1985/spiegelhalter1985uai-probabilistic/) doi:10.1016/B978-0-444-70058-2.50009-7BibTeX
@inproceedings{spiegelhalter1985uai-probabilistic,
title = {{Probabilistic Reasoning in Predictive Expert Systems}},
author = {Spiegelhalter, David J.},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1985},
pages = {47-68},
doi = {10.1016/B978-0-444-70058-2.50009-7},
url = {https://mlanthology.org/uai/1985/spiegelhalter1985uai-probabilistic/}
}