Possibilistic Causal Networks for Handling Interventions: A New Propagation Algorithm
Abstract
This paper contains two important contributions for the development of possibilistic causal networks. The first one concerns the representation of interventions in possibilistic networks. We provide the counterpart of the ”DO ” operator, recently introduced by Pearl, in possibility theory framework. We then show that interventions can equivalently be represented in different ways in possibilistic causal networks. The second main contribution is a new propagation algorithm for dealing with both observations and interventions. We show that our algorithm only needs a small extra cost for handling interventions and is more appropriate for handling sequences of observations and interventions.
Cite
Text
Benferhat and Smaoui. "Possibilistic Causal Networks for Handling Interventions: A New Propagation Algorithm." AAAI Conference on Artificial Intelligence, 2007.Markdown
[Benferhat and Smaoui. "Possibilistic Causal Networks for Handling Interventions: A New Propagation Algorithm." AAAI Conference on Artificial Intelligence, 2007.](https://mlanthology.org/aaai/2007/benferhat2007aaai-possibilistic/)BibTeX
@inproceedings{benferhat2007aaai-possibilistic,
title = {{Possibilistic Causal Networks for Handling Interventions: A New Propagation Algorithm}},
author = {Benferhat, Salem and Smaoui, Salma},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2007},
pages = {373-378},
url = {https://mlanthology.org/aaai/2007/benferhat2007aaai-possibilistic/}
}