Daniel Hein

ORCID

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 27

Top Venues

CoRR

GECCO (Companion)

Eng. Appl. Artif. Intell.

SSCI

Technical University of Munich, Germany (PHD)

Education History

Technical University of Munich, Germany

PHD

Publications

Simon Eisenmann, Daniel Hein, Steffen Udluft, Thomas A. Runkler
Model-based Offline Quantum Reinforcement Learning. CoRR (2024)
Philipp Wissmann, Daniel Hein, Steffen Udluft, Volker Tresp
Why long model-based rollouts are no reason for bad Q-value estimates. CoRR (2024)
Simon Wiedemann, Daniel Hein, Steffen Udluft, Christian B. Mendl
Quantum Policy Iteration via Amplitude Estimation and Grover Search - Towards Quantum Advantage for Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)
Marc Weber, Phillip Swazinna, Daniel Hein, Steffen Udluft, Volkmar Sterzing
Learning Control Policies for Variable Objectives from Offline Data. SSCI (2023)
Marc Weber, Phillip Swazinna, Daniel Hein, Steffen Udluft, Volkmar Sterzing
Learning Control Policies for Variable Objectives from Offline Data. CoRR (2023)
Volker Tresp, Steffen Udluft, Daniel Hein, Werner Hauptmann, Martin Leib, Christopher Mutschler, Daniel D. Scherer, Wolfgang Mauerer
Workshop Summary: Quantum Machine Learning. QCE (2023)
Phillip Swazinna, Steffen Udluft, Daniel Hein, Thomas A. Runkler
Comparing Model-free and Model-based Algorithms for Offline Reinforcement Learning. CoRR (2022)
Henri Meess, Jeremias Gerner, Daniel Hein, Stefanie Schmidtner, Gordon Elger
Reinforcement Learning for Traffic Signal Control Optimization: A Concept for Real-World Implementation. AAMAS (2022)
Simon Wiedemann, Daniel Hein, Steffen Udluft, Christian Mendl
Quantum Policy Iteration via Amplitude Estimation and Grover Search - Towards Quantum Advantage for Reinforcement Learning. CoRR (2022)
Phillip Swazinna, Steffen Udluft, Daniel Hein, Thomas A. Runkler
Behavior Constraining in Weight Space for Offline Reinforcement Learning. ESANN (2021)
Phillip Swazinna, Steffen Udluft, Daniel Hein, Thomas A. Runkler
Behavior Constraining in Weight Space for Offline Reinforcement Learning. CoRR (2021)
Daniel Hein, Daniel Labisch
Trustworthy AI for process automation on a Chylla-Haase polymerization reactor. GECCO Companion (2021)
Daniel Hein, Daniel Labisch
Trustworthy AI for Process Automation on a Chylla-Haase Polymerization Reactor. CoRR (2021)
Daniel Hein, Steffen Limmer, Thomas A. Runkler
Interpretable Control by Reinforcement Learning. CoRR (2020)
Daniel Hein, Steffen Udluft, Thomas A. Runkler
Generating interpretable reinforcement learning policies using genetic programming. GECCO (Companion) (2019)
Daniel Hein, Steffen Udluft, Thomas A. Runkler
Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming. CoRR (2018)
Daniel Hein, Steffen Udluft, Thomas A. Runkler
Interpretable policies for reinforcement learning by genetic programming. Eng. Appl. Artif. Intell. 76 (2018)
Daniel Hein, Steffen Udluft, Thomas A. Runkler
Generating interpretable fuzzy controllers using particle swarm optimization and genetic programming. GECCO (Companion) (2018)
Daniel Hein, Steffen Udluft, Thomas A. Runkler
Interpretable Policies for Reinforcement Learning by Genetic Programming. CoRR (2017)
Daniel Hein, Steffen Udluft, Michel Tokic, Alexander Hentschel, Thomas A. Runkler, Volkmar Sterzing
Batch Reinforcement Learning on the Industrial Benchmark: First Experiences. CoRR (2017)
Daniel Hein, Steffen Udluft, Michel Tokic, Alexander Hentschel, Thomas A. Runkler, Volkmar Sterzing
Batch reinforcement learning on the industrial benchmark: First experiences. IJCNN (2017)
Daniel Hein, Stefan Depeweg, Michel Tokic, Steffen Udluft, Alexander Hentschel, Thomas A. Runkler, Volkmar Sterzing
A Benchmark Environment Motivated by Industrial Control Problems. CoRR (2017)
Daniel Hein, Alexander Hentschel, Thomas A. Runkler, Steffen Udluft
Particle swarm optimization for generating interpretable fuzzy reinforcement learning policies. Eng. Appl. Artif. Intell. 65 (2017)
Daniel Hein, Stefan Depeweg, Michel Tokic, Steffen Udluft, Alexander Hentschel, Thomas A. Runkler, Volkmar Sterzing
A benchmark environment motivated by industrial control problems. SSCI (2017)
Daniel Hein, Alexander Hentschel, Volkmar Sterzing, Michel Tokic, Steffen Udluft
Introduction to the "Industrial Benchmark". CoRR (2016)
Daniel Hein, Alexander Hentschel, Thomas A. Runkler, Steffen Udluft
Reinforcement Learning with Particle Swarm Optimization Policy (PSO-P) in Continuous State and Action Spaces. Int. J. Swarm Intell. Res. 7 (3) (2016)
Daniel Hein, Alexander Hentschel, Thomas A. Runkler, Steffen Udluft
Particle Swarm Optimization for Generating Fuzzy Reinforcement Learning Policies. CoRR (2016)

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Publication Activity (10 Years)

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Daniel Hein