Explanation, irrelevance and statistical independence
Solomon Eyal Shimony · National Conference on Artificial Intelligence · 1991
We evaluate current explanation schemes. These are either insufficiently general, or suffer from other serious drawbacks. We propose a domain-independent explanation system that is based on ignoring irrelevant variables in a probabilistic setting. We then prove important properties of some specific irrelevance-based schemes and discuss how to implement them.