An effective algorithm for incompatibility abduction problems

In the last decade, abduction has been a very active research area. This results in a variety of models mechanizing abduction, namely within a probabilistic or logical framework. Recently, a few abductive models have been proposed within a neural framework. Unfortunately, these neural-/probabilistic-/logical-based models focus on the most simple class, called independent abduction problems. In this paper, we propose a neural-based model to deal with incompatibility abduction problems. To our knowledge, our model is the first one able to efficiently generate best explanations to the complex class of incompatibility abduction problems