Simplifying Explanations in Bayesian Belief Networks

@article{Campos2001SimplifyingEI,
  title={Simplifying Explanations in Bayesian Belief Networks},
  author={Luis M. de Campos and Jos{\'e} A. G{\'a}mez and Seraf{\'i}n Moral},
  journal={International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
  year={2001},
  volume={9},
  pages={461-490}
}
Abductive inference in Bayesian belief networks is intended as the process of generating the K most probable conngurations given an observed evidence. These conngurations are called explanations and in most of the approaches found in the literature, all the explanations have the same number of literals. In this paper we study how to simplify the explanations in such a way that the resulting conngurations are still accounting for the observed facts. 

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