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Publications

Displaying results 241 to 250 of 572.
  1. Riad Akrour; Davide Tateo; Jan Peters

    Continuous Action Reinforcement Learning From a Mixture of Interpretable Experts

    In: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 44, No. 10, Pages 6795-6806, IEEE, 2022.

  2. Fabio Muratore; Fabio Ramos; Greg Turk; Wenhao Yu; Michael Gienger; Jan Peters

    Robot Learning From Randomized Simulations: A Review

    In: Frontiers in Robotics and AI, Vol. 9, Pages 0-10, Frontiers, 2022.

  3. Daniel Tanneberg; Alexandros Paraschos; Jan Peters; Elmar Rueckert

    Deep spiking networks for model-based planning in humanoids

    In: 16th IEEE-RAS International Conference on Humanoid Robots. IEEE-RAS International Conference on Humanoid Robots (Humanoids-2016), November 15-17, Cancun, Mexico, Pages 656-661, IEEE, 2016.

  4. Simone Parisi; Simon Ramstedt; Jan Peters

    Goal-driven dimensionality reduction for reinforcement learning

    In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2017), September 24-28, Vancouver, BC, Canada, Pages 4634-4639, IEEE, 2017.

  5. Hany Abdulsamad; Oleg Arenz; Jan Peters; Gerhard Neumann

    State-Regularized Policy Search for Linearized Dynamical Systems

    In: Laura Barbulescu; Jeremy Frank; Mausam; Stephen F. Smith (Hrsg.). Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling. International Conference on Automated Planning and Scheduling (ICAPS-2017), June 18-23, Pittsburgh, Pennsylvania, USA, Pages 419-424, AAAI Press, 2017.

  6. Riad Akrour; Filipe Veiga; Jan Peters; Gerhard Neumann

    Regularizing Reinforcement Learning with State Abstraction

    In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2018), October 1-5, Madrid, Spain, Pages 534-539, IEEE, 2018.

  7. Paavo Parmas; Carl Edward Rasmussen; Jan Peters; Kenji Doya

    PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

    In: Jennifer G. Dy; Andreas Krause (Hrsg.). Proceedings of the 35th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2018), July 10-15, Stockholm, Sweden, Pages 4062-4071, Proceedings of Machine Learning Research, Vol. 80, PMLR, 2018.

  8. Michael Lutter; Kim Listmann; Jan Peters

    Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems

    In: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2019), November 3-8, Macau, China, Pages 7718-7725, IEEE, 2019.

  9. Michael Lutter; Christian Ritter; Jan Peters

    Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning

    In: 7th International Conference on Learning Representations. International Conference on Learning Representations (ICLR-2019), May 6-9, New Orleans, LA, USA, OpenReview.net, 2019.

  10. Riad Akrour; Davide Tateo; Jan Peters

    Reinforcement Learning from a Mixture of Interpretable Experts

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2006.05911, Pages 0-10, arXiv, 2020.