Temporal Numeric Planning with Patterns
This work addresses temporal numeric planning for AI researchers, but it is incremental as it builds on existing methods.
The authors tackled the problem of temporal numeric planning by extending the planning with patterns approach to handle temporal constraints, and demonstrated strong performance with required concurrency across 10 domains.
We consider temporal numeric planning problems $Π$ expressed in PDDL2.1 level 3, and show how to produce SMT formulas $(i)$ whose models correspond to valid plans of $Π$, and $(ii)$ that extend the recently proposed planning with patterns approach from the numeric to the temporal case. We prove the correctness and completeness of the approach and show that it performs very well on 10 domains with required concurrency.