Paul Höft
PhD Student
About Me
I am a Ph.D. student at Linköping University, Sweden. I work at the Artificial Intelligence & Integrated Computer Systems Division (AIICS) in the Machine Reasoning Lab. My main research interests are optimal classical planning and machine learning.
Short bio
I finished my bachelor's and master's degree at the University of Basel in 2019 and 2021 respectively and joined the Machine Reasoning Lab in September of 2021.
Awards
- Winner, Deterministic Optimal Track for the Ragnarok planner with Dominik Drexler, Daniel Gnad, Jendrik Seipp, David Speck, and Simon Ståhlberg at the 10th International Planning Competition (IPC 2023) at ICAPS 2023.
Publications
2024
Paul Höft, David Speck, Florian Pommerening and Jendrik Seipp.
Versatile Cost Partitioning with Exact Sensitivity Analysis.
In Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling (ICAPS 2024). 2024.
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2023
Paul Höft, David Speck and Jendrik Seipp.
Sensitivity Analysis for Saturated Post-hoc Optimization in Classical Planning.
In Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), pp. 1044–1051. 2023.
paper slides poster 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 citationPaul Höft, David Speck and Jendrik Seipp.
Dofri.
In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
paper citationDavid Speck, Paul Höft, Daniel Gnad and Jendrik Seipp.
Finding Matrix Multiplication Algorithms with Classical Planning — Extended Abstract.
In The 35th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS). 2023.
paper code citation (Superseded by the ICAPS 2023 paper with the same name.)David Speck, Paul Höft, Daniel Gnad and Jendrik Seipp.
Finding Matrix Multiplication Algorithms with Classical Planning.
In Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling (ICAPS 2023), pp. 411–416. 2023.
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