An efficient LP-based admissible heuristic for cost-based abduction

Abstract

Cost-based abduction (CBA) is an important problem in reasoning under uncertainty. The CBA problem is NP-hard, and existing techniques have exponential worst-case complexity. This paper presents an admissible heuristic for CBA based on the use of linear programming to obtain an optimistic estimate of the cost-to-goal. The article then presents empirical results that indicate that the authors' method is efficient in comparison to Santos‘ integer linear programming method.