Suboptimal dynamic programming with error bounds

This paper presents a method to relax dynamic programming. The method makes it possible to find suboptimal solutions with known error bounds to hard problems. The bounds are chosen by the user, who can then effectively trade-off between solution time and accuracy. Several examples from different domains where the method is highly useful are presented.