Tateo, Davide

11 publications

NeurIPS 2024 A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-World Robotics Puze Liu, Jonas Günster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Marić, Sylvain Calinon, Andrej Orsula, Miguel Olivares-Mendez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan Peters
CoRL 2024 Bridging the Gap Between Learning-to-Plan, Motion Primitives and Safe Reinforcement Learning Piotr Kicki, Davide Tateo, Puze Liu, Jonas Günster, Jan Peters, Krzysztof Walas
CoRL 2024 Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning Jonas Günster, Puze Liu, Jan Peters, Davide Tateo
CoRL 2024 One Policy to Run Them All: An End-to-End Learning Approach to Multi-Embodiment Locomotion Nico Bohlinger, Grzegorz Czechmanowski, Maciej Piotr Krupka, Piotr Kicki, Krzysztof Walas, Jan Peters, Davide Tateo
ICLR 2024 Time-Efficient Reinforcement Learning with Stochastic Stateful Policies Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo
ICLR 2023 LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters
AISTATS 2022 Dimensionality Reduction and Prioritized Exploration for Policy Search Marius Memmel, Puze Liu, Davide Tateo, Jan Peters
MLOSS 2021 MushroomRL: Simplifying Reinforcement Learning Research Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
CoRL 2021 Robot Reinforcement Learning on the Constraint Manifold Puze Liu, Davide Tateo, Haitham Bou Ammar, Jan Peters
ICLR 2020 Sharing Knowledge in Multi-Task Deep Reinforcement Learning Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
AAAI 2018 Multiagent Connected Path Planning: PSPACE-Completeness and How to Deal with It Davide Tateo, Jacopo Banfi, Alessandro Riva, Francesco Amigoni, Andrea Bonarini