Using the Probabilistic Logic Programming Language P-Log for Causal and Counterfactual Reasoning and Non-Naive Conditioning
Abstract
P-log is a probabilistic logic programming language, which combines both logic programming style knowledge representation and probabilistic reasoning. In earlier papers various advantages of P-log have been discussed. In this paper we further elaborate on the KR prowess of P-log by showing that: (i) it can be used for causal and counterfactual reasoning and (ii) it provides an elaboration tolerant way for non-naive conditioning.
Cite
Text
Baral and Hunsaker. "Using the Probabilistic Logic Programming Language P-Log for Causal and Counterfactual Reasoning and Non-Naive Conditioning." International Joint Conference on Artificial Intelligence, 2007.Markdown
[Baral and Hunsaker. "Using the Probabilistic Logic Programming Language P-Log for Causal and Counterfactual Reasoning and Non-Naive Conditioning." International Joint Conference on Artificial Intelligence, 2007.](https://mlanthology.org/ijcai/2007/baral2007ijcai-using/)BibTeX
@inproceedings{baral2007ijcai-using,
title = {{Using the Probabilistic Logic Programming Language P-Log for Causal and Counterfactual Reasoning and Non-Naive Conditioning}},
author = {Baral, Chitta and Hunsaker, Matt},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2007},
pages = {243-249},
url = {https://mlanthology.org/ijcai/2007/baral2007ijcai-using/}
}