Unchaining the Power of Partial Delete Relaxation, Part II: Finding Plans with Red-Black State Space Search

Abstract

Red-black relaxation in classical planning allows to interpolate between delete-relaxed and real planning. Yet the traditional use of relaxations to generate heuristics restricts relaxation usage to tractable fragments. How to actually tap into the red-black relaxation's interpolation power? Prior work has devised red-black state space search (RBS) for intractable red-black planning, and has explored two uses: proving unsolvability, generating seed plans for plan repair. Here, we explore the generation of plans directly through RBS. We design two enhancements to this end: (A) use a known tractable fragment where possible, use RBS for the intractable parts; (B) check RBS state transitions for realizability, spawn relaxation refinements where the check fails. We show the potential merits of both techniques on IPC benchmarks.

A Novel Lookahead Strategy for Delete Relaxation Heuristics in Greedy Best-First Search

“…Partial delete relaxation methods aim to mitigate these drawbacks by considering some delete information. Two such techniques are red-black planning (Domshlak, Hoffmann, and Katz 2015;Fickert, Gnad, and Hoffmann 2018), where some state variables are un-relaxed, and partial delete relaxation with explicit conjunctions (Haslum 2012;Keyder, Hoffmann, and Haslum 2012;Fickert, Hoffmann, and Steinmetz 2016), where some combinations of facts are treated atomically.…”