Marie Ossenkopf (M.Sc. RWTH)

Researcher/PhD Student
Address Wilhelmshöher Allee 73
34121 Kassel
Room 1406B
Telephone +49 561 804-6280
Telefax +49 561 804-6277
Office Hours:

by appointment

Picture of  Marie (M.Sc. RWTH) Ossenkopf


  1. Ossenkopf, Marie ; Jorgensen, Mackenzie ; Geihs, Kurt: When Does Communication Learning Need Hierarchical Multi-Agent Deep Reinforcement Learning. In: Cybernetics and Systems vol. 50, Taylor & Francis (2019), Nr. 8, pp. 672-692
  2. Ossenkopf, Marie ; Jorgensen, Mackenzie ; Geihs, Kurt: Hierarchical Multi-Agent Deep Reinforcement Learning to Develop Long-Term Coordination. In: Proceedings of the 34th Annual ACM Symposium on Applied Computing SAC (2019)
  3. Ossenkopf, Marie ; Castro, Gastón ; Pessacg, Facundo ; Geihs, Kurt ; De Cristóforis, Pablo: Long-Horizon Active SLAM system for multi-agent coordinated exploration. In: 2019 European Conference on Mobile Robots (ECMR) : IEEE, 2019, p. 1--6
  4. Beuermann, Maximilian; Ossenkopf, Marie; Geihs, Kurt: Positioning of Active Wheels for Optimal Ball Handling. Robot World Cup. Springer, Cham, 2019.

  5. Opfer, Stephan ; Ossenkopf, Marie ; Geihs, Kurt: Student Competition Teams: Combining

    Research and Teaching. In: Proceedings of the 47th Annual Conference of the Southern African Computer Lecturers' Association, SACLA 2018. Cape Town, South Africa, 2018

  6. Ossenkopf, Marie ; Ennen, Philipp ; Vossen, Rene ; Jeschke, Sabina: Reinforcement Learning for Manipulators without Direct Obstacle Perception in Physically Constrained Environments. In: Procedia Manufacturing vol. 11, Elsevier (2017), p. 329--337