@inproceedings{schumacher2023:deprl,
  title = {DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems},
  booktitle = {The Eleventh International Conference on Learning Representations (ICLR)},
  abstract = {Muscle-actuated organisms are capable of learning an unparalleled diversity of
  dexterous movements despite their vast amount of muscles. Reinforcement learning (RL) on large musculoskeletal models, however, has not been able to show
  similar performance. We conjecture that ineffective exploration in large overactuated action spaces is a key problem. This is supported by our finding that common
  exploration noise strategies are inadequate in synthetic examples of overactuated
  systems. We identify differential extrinsic plasticity (DEP), a method from the
  domain of self-organization, as being able to induce state-space covering exploration within seconds of interaction. By integrating DEP into RL, we achieve fast
  learning of reaching and locomotion in musculoskeletal systems, outperforming
  current approaches in all considered tasks in sample efficiency and robustness.},
  month = may,
  year = {2023},
  author = {Schumacher, Pierre and Haeufle, Daniel F.B. and B{\"u}chler, Dieter and Schmitt, Syn and Martius, Georg},
  url = {https://openreview.net/forum?id=C-xa_D3oTj6},
  month_numeric = {5}
}