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Simon Hirlaender
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2020 – today
- 2025
- [c2]Sabrina Pochaba, Peter Dorfinger, Matthias Herlich, Roland Kwitt, Simon Hirlaender:
Ph.D. Forum: Multi-Agent Reinforcement Learning in Wireless Network Communication. WoWMoM 2025: 317-318 - 2024
- [i5]Georg Schäfer, Max Schirl, Jakob Rehrl, Stefan Huber, Simon Hirlaender:
Python-Based Reinforcement Learning on Simulink Models. CoRR abs/2405.08567 (2024) - [i4]Georg Schäfer, Jakob Rehrl, Stefan Huber, Simon Hirlaender:
Comparison of Model Predictive Control and Proximal Policy Optimization for a 1-DOF Helicopter System. CoRR abs/2408.15633 (2024) - 2023
- [j2]Francesco Velotti, Brennan Goddard, Verena Kain, Rebecca Louise Ramjiawan, Giovanni Zevi Della Porta, Simon Hirlaender:
Towards automatic setup of 18 MeV electron beamline using machine learning. Mach. Learn. Sci. Technol. 4(2): 25016 (2023) - [c1]Reuf Kozlica, Stefan Wegenkittl, Simon Hirländer:
Deep Q-Learning versus Proximal Policy Optimization: Performance Comparison in a Material Sorting Task. ISIE 2023: 1-6 - [i3]Reuf Kozlica, Georg Schäfer, Simon Hirländer, Stefan Wegenkittl:
A Modular Test Bed for Reinforcement Learning Incorporation into Industrial Applications. CoRR abs/2306.01440 (2023) - [i2]Reuf Kozlica, Stefan Wegenkittl, Simon Hirländer:
Deep Q-Learning versus Proximal Policy Optimization: Performance Comparison in a Material Sorting Task. CoRR abs/2306.01451 (2023) - 2021
- [j1]Niky Bruchon, Gianfranco Fenu, Giulio Gaio, Simon Hirlaender, Marco Lonza, Felice Andrea Pellegrino, Erica Salvato:
An Online Iterative Linear Quadratic Approach for a Satisfactory Working Point Attainment at FERMI. Inf. 12(7): 262 (2021) - 2020
- [i1]Simon Hirlaender, Niky Bruchon:
Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FEL. CoRR abs/2012.09737 (2020)
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