Tensor-based abduction in horn propositional programs

Abstract

This paper proposes an algorithm for computing solutions of abductive Horn propositional tasks using third-order tensors. We first introduce the notion of explanatory operator, a single-step operation based on inverted implication, and prove that minimal abductive solutions of a given Horn propositional task can be correctly computed using this operator. We then provide a mapping of Horn propositional programs into third-order tensors, which builds upon recent work on matrix representation of Horn programs. We finally show how this mapping can be used to compute the explanatory operator by tensor multiplication.