Parallel Lifted Planning via Semi-Naive Datalog Evaluation
Lifted classical planners operate directly on first-order planning tasks to avoid the computationally demanding grounding step. However, lifted planning is typically slower, as planners must repeatedly instantiate ground structures during search. Many core components of lifted classical planning, such as successor generation, axiom evaluation, task grounding, and delete-relaxed heuristics, have previously been studied through the lens of Datalog evaluation. We build upon this line of work and extend it by developing and analyzing an execution model with two levels of parallelism: rule-level parallelism and grounding parallelism. We further specialize this solver for planning-specific work...
| Authors | Dominik Drexler, Oliver Joergensen, Jendrik Seipp |
|---|---|
| Primary category | cs.AI |
| Published | 8 May 2026 |
| Last updated at source | 8 May 2026 |
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