How Occam's Razor Provides a Neat Definition of Direct Causation
Abstract
In this paper we show that the application of Occam's razor to the theory of causal Bayes nets gives us a neat definition of direct causation. In particular we show that Occam's razor implies Woodward's (2003) definition of direct causation, provided suitable intervention variables exist and the causal Markov condition (CMC) is satisfied. We also show how Occam's razor can account for direct causal relationships Woodward style when only stochastic intervention variables are available.
Cite
Text
Gebharter and Schurz. "How Occam's Razor Provides a Neat Definition of Direct Causation." Conference on Uncertainty in Artificial Intelligence, 2014.Markdown
[Gebharter and Schurz. "How Occam's Razor Provides a Neat Definition of Direct Causation." Conference on Uncertainty in Artificial Intelligence, 2014.](https://mlanthology.org/uai/2014/gebharter2014uai-occam/)BibTeX
@inproceedings{gebharter2014uai-occam,
title = {{How Occam's Razor Provides a Neat Definition of Direct Causation}},
author = {Gebharter, Alexander and Schurz, Gerhard},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2014},
pages = {1-10},
url = {https://mlanthology.org/uai/2014/gebharter2014uai-occam/}
}