Summary of a New Normative Theory of Probabilistic Logic
Abstract
By probabilistic logic I mean a normative theory of belief that explains how a body of evidence affects one's degree of belief in a possible hypothesis. A new axiomatization of such a theory is presented which avoids a finite additivity axiom, yet which retains many useful inference rules. Many of the examples of this theory--its models do not use numerical probabilities. Put another way, this article gives sharper answers to the two questions: 1.What kinds of sets can used as the range of a probability function? 2.Under what conditions is the range set of a probability function isomorphic to the set of real numbers in the interval 10,1/ with the usual arithmetical operations?
Cite
Text
Aleliunas. "Summary of a New Normative Theory of Probabilistic Logic." Conference on Uncertainty in Artificial Intelligence, 1988.Markdown
[Aleliunas. "Summary of a New Normative Theory of Probabilistic Logic." Conference on Uncertainty in Artificial Intelligence, 1988.](https://mlanthology.org/uai/1988/aleliunas1988uai-summary/)BibTeX
@inproceedings{aleliunas1988uai-summary,
title = {{Summary of a New Normative Theory of Probabilistic Logic}},
author = {Aleliunas, Romas},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1988},
url = {https://mlanthology.org/uai/1988/aleliunas1988uai-summary/}
}