Computing Reference Classes
Artificial Intelligence
2013-04-12 v1
Abstract
For any system with limited statistical knowledge, the combination of evidence and the interpretation of sampling information require the determination of the right reference class (or of an adequate one). The present note (1) discusses the use of reference classes in evidential reasoning, and (2) discusses implementations of Kyburg's rules for reference classes. This paper contributes the first frank discussion of how much of Kyburg's system is needed to be powerful, how much can be computed effectively, and how much is philosophical fat.
Cite
@article{arxiv.1304.3099,
title = {Computing Reference Classes},
author = {Ronald P. Loui},
journal= {arXiv preprint arXiv:1304.3099},
year = {2013}
}
Comments
Appears in Proceedings of the Second Conference on Uncertainty in Artificial Intelligence (UAI1986)