Dominik Drexler
Postdoctoral Researcher
About Me
My primary research interest is in artificial intelligence, with a focus on integrating machine learning and automated planning to improve the scalability of AI planning systems. For example, by learning general solution strategies that enable goal-directed acting with minimal to no search effort. I am also a core developer of Mimir, a generalized planning library designed to address this challenge.
Short bio
I finished my bachelor's and master's degree in computer science at the University of Freiburg in 2017 and 2020 respectively. From November 2020, I was a PhD student in the Machine Reasoning Lab at Linköping University under the supervision of Prof. Dr. Hector Geffner (main) and Prof. Dr. Jendrik Seipp (co) and received my PhD in March 2025. Currently, I am a postdoctoral researcher in the same group at Linköping University.
Awards
- Lawson Scholarship 2024 for outstanding research contributions during PhD studies awarded by the Linköping University.
- Winner, Deterministic Optimal Track for the Ragnarok planner with Daniel Gnad, Paul Höft, Jendrik Seipp, David Speck, and Simon Ståhlberg at the 10th International Planning Competition (IPC 2023) at ICAPS 2023.
Publications
2024
Dominik Drexler, Simon Ståhlberg, Blai Bonet and Hector Geffner.
Symmetries and Expressive Requirements for Learning General Policies.
In Proceedings of the Twenty-First International Conference on Principles of Knowledge Representation and Reasoning (KR 2024). 2024.
paper slides citationBlai Bonet, Dominik Drexler and Hector Geffner.
On Policy Reuse: An Expressive Language for Representing and Executing General Policies that Call Other Policies.
In Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling (ICAPS 2024), pp. 31–39. 2024.
paper slides citationDominik Drexler, Simon Ståhlberg, Blai Bonet and Hector Geffner.
Equivalence-Based Abstractions for Learning General Policies.
In ICAPS 2024 Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL). 2024.
paper slides citationDominik Drexler, Jendrik Seipp and Hector Geffner.
Expressing and Exploiting Subgoal Structure in Classical Planning Using Sketches.
Journal of Artificial Intelligence Research 80, pp. 171–208. 2024.
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2023
Blai Bonet, Dominik Drexler and Hector Geffner.
General and Reusable Indexical Policies and Sketches.
In NeurIPS 2023 Workshop on Generalization in Planning. 2023.
paper code citationDominik Drexler, Jendrik Seipp and Hector Geffner.
Learning Hierarchical Policies by Iteratively Reducing the Width of Sketch Rules.
In Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning (KR 2023), pp. 208–218. 2023.
paper slides code citationDominik Drexler, Daniel Gnad, Paul Höft, Jendrik Seipp, David Speck and Simon Ståhlberg.
Ragnarok.
In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
paper citationDominik Drexler, Jendrik Seipp and David Speck.
Odin: A Planner Based on Saturated Transition Cost Partitioning.
In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
paper citationDominik Drexler and Jendrik Seipp.
DLPlan: Description Logics State Features for Planning.
In ICAPS 2023 System Demonstrations and Exhibits. 2023.
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2022
Dominik Drexler, Javier Segovia-Aguas and Jendrik Seipp.
Learning General Policies and Helpful Action Classifiers from Partial State Spaces.
In IJCAI 2022 Workshop on Generalization in Planning. 2022.
paper slides citationDominik Drexler, Jendrik Seipp and Hector Geffner.
Learning Sketches for Decomposing Planning Problems into Subproblems of Bounded Width.
In Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling (ICAPS 2022), pp. 62–70. 2022.
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2021
Dominik Drexler, Jendrik Seipp and Hector Geffner.
Expressing and Exploiting the Common Subgoal Structure of Classical Planning Domains Using Sketches.
In Proceedings of the Eighteenth International Conference on Principles of Knowledge Representation and Reasoning (KR 2021), pp. 258–268. 2021.
paper slides recording poster citationDominik Drexler, Jendrik Seipp and David Speck.
Subset-Saturated Transition Cost Partitioning.
In Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling (ICAPS 2021), pp. 131–139. 2021.
paper slides poster code citation