Simon Hirlaender

According to our database, Simon Hirlaender authored at least 10 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Multi-Objective Reinforcement Learning for Energy-Efficient Industrial Control.

Georg Schäfer, Raphael Seliger, Jakob Rehrl, Stefan Huber, Simon Hirlaender

CoRR, May, 2025

Ph.D. Forum: Multi-Agent Reinforcement Learning in Wireless Network Communication.

Sabrina Pochaba, Peter Dorfinger, Matthias Herlich, Roland Kwitt, Simon Hirlaender

Proceedings of the 25th IEEE International Symposium on a World of Wireless, 2025

The Crucial Role of Problem Formulation in Real-World Reinforcement Learning.

Georg Schäfer, Tatjana Krau, Jakob Rehrl, Stefan Huber, Simon Hirlaender

Proceedings of the 8th IEEE International Conference on Industrial Cyber-Physical Systems, 2025

2024

Python-Based Reinforcement Learning on Simulink Models.

Georg Schäfer, Maximilian Schirl, Jakob Rehrl, Stefan Huber, Simon Hirlaender

CoRR, 2024

Comparison of Model Predictive Control and Proximal Policy Optimization for a 1-DOF Helicopter System.

Georg Schäfer, Jakob Rehrl, Stefan Huber, Simon Hirlaender

Proceedings of the 22nd IEEE International Conference on Industrial Informatics, 2024

2023

Towards automatic setup of 18 MeV electron beamline using machine learning.

Francesco Velotti, Brennan Goddard, Verena Kain, Rebecca Louise Ramjiawan, Giovanni Zevi Della Porta, Simon Hirlaender

Mach. Learn. Sci. Technol., June, 2023

A Modular Test Bed for Reinforcement Learning Incorporation into Industrial Applications.

Reuf Kozlica, Georg Schäfer, Simon Hirländer, Stefan Wegenkittl

CoRR, 2023

Deep Q-Learning versus Proximal Policy Optimization: Performance Comparison in a Material Sorting Task.

Reuf Kozlica, Stefan Wegenkittl, Simon Hirländer

Proceedings of the 32nd IEEE International Symposium on Industrial Electronics, 2023

2021

An Online Iterative Linear Quadratic Approach for a Satisfactory Working Point Attainment at FERMI.

Niky Bruchon, Gianfranco Fenu, Giulio Gaio, Simon Hirlaender, Marco Lonza, Felice Andrea Pellegrino, Erica Salvato

Inf., 2021

2020

Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FEL.

Simon Hirlaender, Niky Bruchon

CoRR, 2020