Causes and Explanations: A Structural-Model Approach --- Part 1: Causes
Artificial Intelligence
2013-01-14 v1
Abstract
We propose a new definition of actual causes, using structural equations to model counterfactuals.We show that the definitions yield a plausible and elegant account ofcausation that handles well examples which have caused problems forother definitions and resolves major difficulties in the traditionalaccount. In a companion paper, we show how the definition of causality can beused to give an elegant definition of (causal) explanation.
Cite
@article{arxiv.1301.2275,
title = {Causes and Explanations: A Structural-Model Approach --- Part 1: Causes},
author = {Joseph Y. Halpern and Judea Pearl},
journal= {arXiv preprint arXiv:1301.2275},
year = {2013}
}
Comments
Appears in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI2001), later extended version is arXiv:cs/0011012