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Publications

Displaying results 381 to 390 of 681.

  1. Carlo D'Eramo; Davide Tateo; Andrea Bonarini; Marcello Restelli; Jan Peters

    Sharing Knowledge in Multi-Task Deep Reinforcement Learning

    In: 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. International Conference on Learning Representations (ICLR), OpenReview.net, 2020.

  2. Sebastián Gómez-González; Sergey Prokudin; Bernhard Schölkopf; Jan Peters

    Real Time Trajectory Prediction Using Deep Conditional Generative Models

    In: IEEE Robotics and Automation Letters (RA-L), Vol. 5, No. 2, Pages 970-976, IEEE, 2020.

  3. Daan Wierstra; Alexander Förster; Jan Peters; Jürgen Schmidhuber

    Solving Deep Memory POMDPs with Recurrent Policy Gradients

    In: Joaquim Marques de Sá; Luís A. Alexandre; Wlodzislaw Duch; Danilo P. Mandic (Hrsg.). Artificial Neural Networks - ICANN 2007, 17th International Conference, Proceedings. International Conference on Artificial Neural Networks (ICANN-2007), September 9-13, Porto, Portugal, Pages 697-706, Lecture Notes in Computer Science, Vol. 4668, Springer, 2007.

  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. Jason Raphael Rambach; Bruno Mirbach; Yuriy Anisimov; Didier Stricker

    Time-of-Flight Depth Sensing for Automotive Safety and Smart Building Applications: The VIZTA Project

    In: IEEE Access (IEEE), Vol. 11, Pages 105819-105829, IEEE, 10/2023.

  9. David Steinmann; Wolfgang Stammer; Felix Friedrich; Kristian Kersting

    Learning to Intervene on Concept Bottlenecks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2308.13453, Pages 0-10, arXiv, 2023.

  10. Quentin Delfosse; Jannis Blüml; Bjarne Gregori; Sebastian Sztwiertnia; Kristian Kersting

    OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2306.08649, Pages 0-10, arXiv, 2023.

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