4 citations · 4 across the 8 of their papers we have counts for
9 papers
Learning How to Search for Plans with Exponentially Less Space
Dominik Drexler, Simon Ståhlberg, Markus Fritzsche +1
Heuristic search for a plan can store exponentially many states, even when its heuristic is almost perfect. We instead learn search control, one specification per domain, written a…
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…
On Policy Reuse: An Expressive Language for Representing and Executing General Policies that Call Other Policies
Blai Bonet, Dominik Drexler, Hector Geffner
Recently, a simple but powerful language for expressing and learning general policies and problem decompositions (sketches) has been introduced in terms of rules defined over a set…
Learning Sketches for Decomposing Planning Problems into Subproblems of Bounded Width: Extended Version
Dominik Drexler, Jendrik Seipp, Hector Geffner
Recently, sketches have been introduced as a general language for representing the subgoal structure of instances drawn from the same domain. Sketches are collections of rules of t…
Expressing and Exploiting the Common Subgoal Structure of Classical Planning Domains Using Sketches: Extended Version
Dominik Drexler, Jendrik Seipp, Hector Geffner
Width-based planning methods deal with conjunctive goals by decomposing problems into subproblems of low width. Algorithms like SIW thus fail when the goal is not easily serializab…