Conditions for Avoiding Node Re-expansions in Bounded Suboptimal Search

Many practical problems are too difficult to solve optimally, motivating the need to found suboptimal solutions, particularly those with bounds on the final solution quality. Algorithms like Weighted A*, A*-epsilon, Optimistic Search, EES, and DPS have been developed to find suboptimal solutions with solution quality that is within a constant bound of the optimal solution. However, with the exception of weighted A*, all of these algorithms require performing node re-expansions during search. This paper explores the properties of priority functions that can find bounded suboptimal solution without requiring node re-expansions. After general bounds are developed, two new convex priority functions are developed that can outperform weighted A*.