Improving Jump Point Search - Harabor, Daniel; Grastien, Alban (Proceedings of the International Conference on Automated Planning and Scheduling, 2014)
We give online and offline optimisation techniques to improve the performance of Jump Point Search (JPS): a recent and very effective symmetry-breaking algorithm that speeds up pathfinding in computer games. First, we give a new and more efficient procedure for online symmetry breaking by manipulating "blocks’’ of nodes at a single time rather than individual nodes. Second, we give a new offline pre-processing technique that can identify jump points apriori in order to further speed up pathfinding search. Third, we enhance the pruning rules of JPS, allowing it to ignore many nodes that must otherwise be expanded. On three benchmark domains taken from real computer games we show that our enhancements can improve JPS performance by anywhere from several factors to over one order of magnitude. We also compare our approaches with SUB: a very recent state-of-the-art offline pathfinding algorithm. We show that our improvements are competitive with this approach and often faster.