Open Access
February, 1987 The Probability Approach to the Treatment of Uncertainty in Artificial Intelligence and Expert Systems
Dennis V. Lindley
Statist. Sci. 2(1): 17-24 (February, 1987). DOI: 10.1214/ss/1177013427

Abstract

Arguments are adduced to support the claim that the only satisfactory description of uncertainty is probability. Probability is described both mathematically and interpretatively as a degree of belief. The axiomatic basis and the use of scoring rules in developing coherence are discussed. A challenge is made that anything that can be done by alternative methods for handling uncertainty can be done better by probability. This is demonstrated by some examples using fuzzy logic and belief functions. The paper concludes with a forensic example illustrating the power of probability ideas.

Citation

Download Citation

Dennis V. Lindley. "The Probability Approach to the Treatment of Uncertainty in Artificial Intelligence and Expert Systems." Statist. Sci. 2 (1) 17 - 24, February, 1987. https://doi.org/10.1214/ss/1177013427

Information

Published: February, 1987
First available in Project Euclid: 19 April 2007

zbMATH: 0955.68507
MathSciNet: MR896257
Digital Object Identifier: 10.1214/ss/1177013427

Keywords: Artificial intelligence , Bayes theorem , Belief functions , Coherence , decision-making , expert systems , forensic evidence , fuzzy logic , Probability , scoring rules

Rights: Copyright © 1987 Institute of Mathematical Statistics

Vol.2 • No. 1 • February, 1987
Back to Top