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Dominik Drexler

PhD student

Research interest in artificial intelligence, with a focus on automated planning.

Artificial intelligence, with a focus on automated planning

I am especially interested in the general subgoal structure.

My main research interest is the integration of planning and learning. More specifically, the generalized planning problem where the objective is to learn an algorithm that efficiently solves an infinitely large class of planning problems. In this context, I am especially interested in the general subgoal structure.

CV in brief

I finished my bachelor's and master's degree in computer science at the University of Freiburg in 2017 and 2020 respectively. 
Since November 2020, I have been part of the RLPLAB team at Linköping University, Sweden.

Publications

2024

Dominik Drexler, Simon Ståhlberg, Blai Bonet, Hector Geffner (2024) Symmetries and Expressive Requirements for Learning General Policies Proceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning (KR2024) (Conference paper)
Dominik Drexler, Jendrik Seipp, Hector Geffner (2024) Expressing and Exploiting Subgoal Structure in Classical Planning Using Sketches The journal of artificial intelligence research, Vol. 80, p. 171-208 (Article in journal) Continue to DOI
Blai Bonet, Dominik Drexler, Hector Geffner (2024) On Policy Reuse: An Expressive Language for Representing and Executing General Policies that Call Other Policies Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling (ICAPS 2024) (Conference paper)

2023

Dominik Drexler, Jendrik Seipp, Hector Geffner (2023) Learning Hierarchical Policies by Iteratively Reducing the Width of Sketch Rules 20th International Conference on Principles of Knowledge Representation and Reasoning, Rhodes, Greece, September 2-8, 2023 (Conference paper)

2022

Dominik Drexler, Jendrik Seipp, Hector Geffner (2022) Learning Sketches for Decomposing Planning Problems into Subproblems of Bounded Width Proceedings of the 32nd International Conference on Automated Planning and Scheduling (ICAPS2022), p. 62-70 (Conference paper) Continue to DOI

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