2 papers
cs.LG2026
Impact of Markov Decision Process Design on Sim-to-Real Reinforcement Learning
Tatjana Krau, Jorge Mandlmaier, Tobias Damm +1
Reinforcement Learning (RL) has demonstrated strong potential for industrial process control, yet policies trained in simulation often suffer from a significant sim-to-real gap whe…
eess.SY2025
The Crucial Role of Problem Formulation in Real-World Reinforcement Learning
Georg Schäfer, Tatjana Krau, Jakob Rehrl +2
Reinforcement Learning (RL) offers promising solutions for control tasks in industrial cyber-physical systems (ICPSs), yet its real-world adoption remains limited. This paper demon…