Paul Höft

PhD student

My general research interests are classical planning and machine learning.

Classical planning and machine learning

I focus on optimal classical planning and how to combine it with machine learning.

This includes learning admissible heuristics and advancing existing algorithms through online learning and/or dynamic algorithm configuration.

I completed my bachelor's degree in 2018 and my master's degree 2021 in computer science at the University of Basel and joined the RLPLAB in September 2021.

Publications

2024

Paul Höft, David Speck, David Speck, Jendrik Seipp, Florian Pommerening (2024) Versatile Cost Partitioning with Exact Sensitivity Analysis Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling (ICAPS 2024), p. 276-280 (Conference paper)

2023

Paul Höft, David Speck, Jendrik Seipp (2023) Sensitivity Analysis for Saturated Post-hoc Optimization in Classical Planning Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), p. 1044-1051 (Conference paper)

Continue to DOI

David Speck, Paul Höft, Daniel Gnad, Jendrik Seipp (2023) Finding Matrix Multiplication Algorithms with Classical Planning Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS 2023), p. 411-416 (Conference paper)

About the division

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Artificial Intelligence and Integrated Computer Systems (AIICS)

The AIICS division is part of the Department of Computer and Information Science. The division's main focus is research and teaching in artificial intelligence, its theoretical foundations and its applications.

Colleagues at AIICS

Paul Höft

Classical planning and machine learning

Publications

2024

2023

About the division

Artificial Intelligence and Integrated Computer Systems (AIICS)

Colleagues at AIICS

About the department

Department of Computer and Information Science (IDA)

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