Relative Entropy, Probabilistic Inference and AI
Artificial Intelligence
2013-04-15 v1
Abstract
Various properties of relative entropy have led to its widespread use in information theory. These properties suggest that relative entropy has a role to play in systems that attempt to perform inference in terms of probability distributions. In this paper, I will review some basic properties of relative entropy as well as its role in probabilistic inference. I will also mention briefly a few existing and potential applications of relative entropy to so-called artificial intelligence (AI).
Keywords
Cite
@article{arxiv.1304.3423,
title = {Relative Entropy, Probabilistic Inference and AI},
author = {John E. Shore},
journal= {arXiv preprint arXiv:1304.3423},
year = {2013}
}
Comments
Appears in Proceedings of the First Conference on Uncertainty in Artificial Intelligence (UAI1985)