# Most Relevant Explanation: computational complexity and approximation methods

@article{Yuan2011MostRE,
title={Most Relevant Explanation: computational complexity and approximation methods},
author={Changhe Yuan and Heejin Lim and Michael L. Littman},
journal={Annals of Mathematics and Artificial Intelligence},
year={2011},
volume={61},
pages={159-183}
}
Most Relevant Explanation (MRE) is the problem of finding a partial instantiation of a set of target variables that maximizes the generalized Bayes factor as the explanation for given evidence in a Bayesian network. MRE has a huge solution space and is extremely difficult to solve in large Bayesian networks. In this paper, we first prove that MRE is at least NP-hard. We then define a subproblem of MRE called MRE k that finds the most relevant k-ary explanation and prove that the decision… CONTINUE READING