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Statistical Analysis of Reinforcement Learning Training

In: Operations Research Proceedings 2023

Author

Listed:
  • Maximilian Moll

    (Institute of Operations Research, University of the Bundeswehr Munich)

  • Matthias Schilling

    (Institute of Operations Research, University of the Bundeswehr Munich)

  • Stefan Pickl

    (Institute of Operations Research, University of the Bundeswehr Munich)

Abstract

One of the most urgent challenges in Reinforcement Learning research is the lack of reproducibility. Therefore, to further the understanding of the training behavior of Reinforcement Learning agents, we analyze the training of agents playing the established baseline environment Taxi. In particular, we contrast results based on different forms of exploration. In addition, we can demonstrate that in this context penalization without termination is to be the preferred punishment for incorrect actions.

Suggested Citation

  • Maximilian Moll & Matthias Schilling & Stefan Pickl, 2025. "Statistical Analysis of Reinforcement Learning Training," Lecture Notes in Operations Research, in: Guido Voigt & Malte Fliedner & Knut Haase & Wolfgang Brüggemann & Kai Hoberg & Joern Meissner (ed.), Operations Research Proceedings 2023, chapter 0, pages 447-452, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-58405-3_57
    DOI: 10.1007/978-3-031-58405-3_57
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