ICLR paper accepted

Qi and Marco’s paper got accept for presentation at ICLR. Congratulations! The submitted version is available here, camera-ready version is coming soon.

Two IJCAI papers accepted

Two of our IJCAI submissions were accepted:
With Niklas Höpner & Ilaria Tiddi: Leveraging class abstraction for commonsense reinforcement learning via residual policy gradient methods (pre-print)
With Jan Wöhlke & Felix Schmitt: Value Refinement Network (VRN) (earlier version)
Congrats Jan & Niklas!

CPAIOR paper accepted

Wouter Kool’s paper “Deep policy dynamic programming for vehicle routing problems” was accepted to CPAIOR. Congratulations! A preprint is available on the arXiv.

AAAI paper accepted

Alex Long’s AAAI submission on Fast and Data Efficient Reinforcement Learning from Pixels via Non-Parametric Value Approximation got accepted for presentation! The paper is the result of a collaboration started when Alex visited us at UvA. Congrats, Alex!

Several working papers posted

We’ve recently posted several working papers that I hope you’ll find interesting:

  • Amin, S., Gomrokchi, M., Satija, H., van Hoof, H., & Precup, D. (2021). A Survey of Exploration Methods in Reinforcement Learning. arXiv preprint arXiv:2109.00157.
  • Kool, W., van Hoof, H., Gromicho, J., & Welling, M. (2021). Deep Policy Dynamic Programming for Vehicle Routing Problems. arXiv preprint arXiv:2102.11756.