Causes and Explanations: A Structural-Model Approach. Part II: Explanations
Artificial Intelligence
2007-05-23 v3
Abstract
We propose new definitions of (causal) explanation, using structural equations to model counterfactuals. The definition is based on the notion of actual cause, as defined and motivated in a companion paper. Essentially, an explanation is a fact that is not known for certain but, if found to be true, would constitute an actual cause of the fact to be explained, regardless of the agent's initial uncertainty. We show that the definition handles well a number of problematic examples from the literature.
Cite
@article{arxiv.cs/0208034,
title = {Causes and Explanations: A Structural-Model Approach. Part II: Explanations},
author = {Joseph Y. Halpern and Judea Pearl},
journal= {arXiv preprint arXiv:cs/0208034},
year = {2007}
}
Comments
Part I of the paper (on causes) is also on the arxiv. The two papers originally were posted as one submission. The conference version of the paper appears in IJCAI '01. This paper will appear in the British Journal for Philosophy of Science