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Jahr: 2021
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  1. Fabio Muratore; Michael Gienger; Jan Peters

    Assessing Transferability From Simulation to Reality for Reinforcement Learning

    In: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 43, No. 4, Pages 1172-1183, IEEE, 2021.

  2. Riad Akrour; Asma Atamna; Jan Peters

    Convex optimization with an interpolation-based projection and its application to deep learning

    In: Machine Learning, Vol. 110, No. 8, Pages 2267-2289, Springer, 2021.

  3. Carlo D'Eramo; Andrea Cini; Alessandro Nuara; Matteo Pirotta; Cesare Alippi; Jan Peters; Marcello Restelli

    Gaussian Approximation for Bias Reduction in Q-Learning

    In: Journal of Machine Learning Research, Vol. 22, Pages 277:1-277:51, JMLR, 2021.

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

    MushroomRL: Simplifying Reinforcement Learning Research

    In: Journal of Machine Learning Research, Vol. 22, Pages 131:1-131:5, JMLR, 2021.

  5. Niyati Rawal; Dorothea Koert; Cigdem Turan; Kristian Kersting; Jan Peters; Ruth Stock-Homburg

    ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition

    In: Frontiers in Robotics and AI, Vol. 8, Pages 0-10, Frontiers, 2021.

  6. Bastian Wibranek; Yuxi Liu; Niklas Funk; Boris Belousov; Jan Peters; Oliver Tessmann

    Reinforcement learning for sequential assembly of SL-blocks-self-interlocking combinatorial design based on machine learning

    In: Vesna Stojaković; Bojan Tepavčević (Hrsg.). eCAADe 2021 - Towards a New, Configurable Architecture, Volume 1 - Proceedings. Education and Research …

  7. Hany Abdulsamad; Tim Dorau; Boris Belousov; Jia-Jie Zhu; Jan Peters

    Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative Entropy Trust-Regions

    arXiv preprint arXiv:2103.15388, 2021.

  8. Pascal Klink; Hany Abdulsamad; Boris Belousov; Carlo D'Eramo; Jan Peters; Joni Pajarinen

    A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning

    In: Journal of Machine Learning Research, Vol. 22, Pages 182:1-182:52, JMLR, 2021.

  9. Liudvikas Nemiro; Gerard Canal; Oscar Lima; Michael Cashmore; Mark Roberts

    Designing an Adaptable Benchmark and Competition Simulation for Integrated Planning and Execution

    In: Workshop on the International Planning Competition (WIPC). International Conference on Automated Planning and Scheduling (ICAPS-2021), located at …

  10. Tomás Ribeiro; Oscar Lima; Michael Cashmore; Andrea Micheli; Rodrigo Ventura

    Olisipo: A probabilistic approach to the adaptable execution of deterministic temporal plans

    In: Proceedings of the International Symposium on Temporal Representation and Reasoning. International Symposium on Temporal Representation and …

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