Models and Algorithms for Probabilistic and Bayesian Logic
Abstract
An overview is given, with new results, of mathematical models and algorithms for probabilistic logic, probabilistic entailment and various extensions. Analytical and numerical solutions are considered, the former leading to automated generation of theorems in the theory of probabilities. Ways to restore consistency and relationship with Bayesian networks are also studied.
Cite
Text
Hansen et al. "Models and Algorithms for Probabilistic and Bayesian Logic." International Joint Conference on Artificial Intelligence, 1995.Markdown
[Hansen et al. "Models and Algorithms for Probabilistic and Bayesian Logic." International Joint Conference on Artificial Intelligence, 1995.](https://mlanthology.org/ijcai/1995/hansen1995ijcai-models/)BibTeX
@inproceedings{hansen1995ijcai-models,
title = {{Models and Algorithms for Probabilistic and Bayesian Logic}},
author = {Hansen, Pierre and Jaumard, Brigitte and Nguetsé, Guy-Blaise Douanya and de Aragão, Marcus Poggi},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1995},
pages = {1862-1868},
url = {https://mlanthology.org/ijcai/1995/hansen1995ijcai-models/}
}