Improving Graphplan's Search with EBL & DDB Techniques

I highlight some inefficiencies of Graphplan's backward search algorithm, and describe how these can be eliminated by adding explanation-based learning and dependency-directed backtracking capabilities to Graphplan. I will then demonstrate the effectiveness of these augmentations by describing results of empirical studies that show dramatic improvements in run-time (w 100× speedups) as well as solvability-horizons on benchmark problems across seven different domains.