5 papers · 1 filter
LLM-Evolved Pattern Generators for Optimal Classical Planning
Windy Phung, Dominik Drexler, Arnaud Lequen +1
Learned heuristics have recently become a competitive alternative to traditional domain-independent heuristics for satisficing planning. Existing approaches, however, focus on impr…
Parallel Lifted Planning via Semi-Naive Datalog Evaluation
Dominik Drexler, Oliver Joergensen, Jendrik Seipp
Lifted classical planners operate directly on first-order planning tasks to avoid the computationally demanding grounding step. However, lifted planning is typically slower, as pla…
Dynamic Tree Databases in Automated Planning
Oliver Joergensen, Dominik Drexler, Jendrik Seipp
A central challenge in scaling up explicit state-space search for large tasks is compactly representing the set of generated states. Tree databases, a data structure from model che…
Lifted Successor Generation in Numeric Planning
Dominik Drexler
Most planners ground numeric planning tasks, given in a first-order-like language, into a ground task representation. However, this can lead to an exponential blowup in task repres…
Symmetries and Expressive Requirements for Learning General Policies
Dominik Drexler, Simon Ståhlberg, Blai Bonet +1
State symmetries play an important role in planning and generalized planning. In the first case, state symmetries can be used to reduce the size of the search; in the second, to re…