Davide Tateo

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 44

Top Topics

Markov Decision Process

Reinforcement Learning

Continuous Action

Top Venues

IEEE Robotics Autom. Lett.

Publications

Christopher E. Mower, Yuhui Wan, Hongzhan Yu, Antoine Grosnit, Jonas Gonzalez-Billandon, Matthieu Zimmer, Jinlong Wang, Xinyu Zhang, Yao Zhao, Anbang Zhai, Puze Liu, Davide Tateo, Cesar Cadena, Marco Hutter, Jan Peters, Guangjian Tian, Yuzheng Zhuang, Kun Shao, Xingyue Quan, Jianye Hao, Jun Wang, Haitham Bou-Ammar
ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning. CoRR (2024)
Henri-Jacques Geiß, Firas Al-Hafez, Andre Seyfarth, Jan Peters, Davide Tateo
Exciting Action: Investigating Efficient Exploration for Learning Musculoskeletal Humanoid Locomotion. CoRR (2024)
Piotr Kicki, Puze Liu, Davide Tateo, Haitham Bou-Ammar, Krzysztof Walas, Piotr Skrzypczynski, Jan Peters
Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks. IEEE Trans. Robotics 40 (2024)
Puze Liu, Haitham Bou-Ammar, Jan Peters, Davide Tateo
Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications. CoRR (2024)
Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies. ICLR (2024)
Julius Jankowski, Ante Maric, Puze Liu, Davide Tateo, Jan Peters, Sylvain Calinon
Energy-based Contact Planning under Uncertainty for Robot Air Hockey. CoRR (2024)
Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. CoRR (2024)
Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning. ICLR (2023)
Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo
LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion. CoRR (2023)
Filip Bjelonic, Joonho Lee, Philip Arm, Dhionis V. Sako, Davide Tateo, Jan Peters, Marco Hutter
Learning-Based Design and Control for Quadrupedal Robots With Parallel-Elastic Actuators. IEEE Robotics Autom. Lett. 8 (3) (2023)
Luca Lach, Robert Haschke, Davide Tateo, Jan Peters, Helge J. Ritter, Júlia Borràs Sol, Carme Torras
Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot. CoRR (2023)
Piotr Kicki, Puze Liu, Davide Tateo, Haitham Bou-Ammar, Krzysztof Walas, Piotr Skrzypczynski, Jan Peters
Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks. CoRR (2023)
Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies. CoRR (2023)
Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Zhiyuan Hu, Jan Peters, Georgia Chalvatzaki
Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction. ICRA (2023)
Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning. CoRR (2023)
Filip Bjelonic, Joonho Lee, Philip Arm, Dhionis Sako, Davide Tateo, Jan Peters, Marco Hutter
Learning-based Design and Control for Quadrupedal Robots with Parallel-Elastic Actuators. CoRR (2023)
Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning. Algorithms 15 (3) (2022)
Marius Memmel, Puze Liu, Davide Tateo, Jan Peters
Dimensionality Reduction and Prioritized Exploration for Policy Search. CoRR (2022)
Marius Memmel, Puze Liu, Davide Tateo, Jan Peters
Dimensionality Reduction and Prioritized Exploration for Policy Search. AISTATS (2022)
Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Jan Peters, Georgia Chalvatzaki
Regularized Deep Signed Distance Fields for Reactive Motion Generation. CoRR (2022)
Julen Urain, Davide Tateo, Jan Peters
Learning Stable Vector Fields on Lie Groups. IEEE Robotics Autom. Lett. 7 (4) (2022)
Riad Akrour, Davide Tateo, Jan Peters
Continuous Action Reinforcement Learning From a Mixture of Interpretable Experts. IEEE Trans. Pattern Anal. Mach. Intell. 44 (10) (2022)
Davide Tateo, Davide Antonio Cucci, Matteo Matteucci, Andrea Bonarini
Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping. CoRR (2022)
Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Zhiyuan Hu, Jan Peters, Georgia Chalvatzaki
Safe reinforcement learning of dynamic high-dimensional robotic tasks: navigation, manipulation, interaction. CoRR (2022)
Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Jan Peters, Georgia Chalvatzaki
Regularized Deep Signed Distance Fields for Reactive Motion Generation. IROS (2022)
João Carvalho, Davide Tateo, Fabio Muratore, Jan Peters
An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients. CoRR (2021)
Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters
Efficient and Reactive Planning for High Speed Robot Air Hockey. CoRR (2021)
João Carvalho, Davide Tateo, Fabio Muratore, Jan Peters
An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients. IJCNN (2021)
Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters
Robot Reinforcement Learning on the Constraint Manifold. CoRL (2021)
Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
MushroomRL: Simplifying Reinforcement Learning Research. J. Mach. Learn. Res. 22 (2021)
Julen Urain, Davide Tateo, Jan Peters
Learning Stable Vector Fields on Lie Groups. CoRR (2021)
Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters
Efficient and Reactive Planning for High Speed Robot Air Hockey. IROS (2021)
Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
MushroomRL: Simplifying Reinforcement Learning Research. CoRR (2020)
Julen Urain, Michele Ginesi, Davide Tateo, Jan Peters
ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows. IROS (2020)
Julen Urain, Davide Tateo, Tianyu Ren, Jan Peters
Structured Policy Representation: Imposing Stability in arbitrarily conditioned dynamic systems. CoRR (2020)
Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Long-Term Visitation Value for Deep Exploration in Sparse Reward Reinforcement Learning. CoRR (2020)
Julen Urain, Michele Ginesi, Davide Tateo, Jan Peters
ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows. CoRR (2020)
Riad Akrour, Davide Tateo, Jan Peters
Reinforcement Learning from a Mixture of Interpretable Experts. CoRR (2020)
Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. ICLR (2020)
Davide Tateo, Idil Su Erdenlig, Andrea Bonarini
Graph-Based Design of Hierarchical Reinforcement Learning Agents. IROS (2019)
Carolina Beretta, Cecilia Brizzolari, Davide Tateo, Alessandro Riva, Francesco Amigoni
A Sampling-Based Algorithm for Planning Smooth Nonholonomic Paths. ECMR (2019)
Davide Tateo, Jacopo Banfi, Alessandro Riva, Francesco Amigoni, Andrea Bonarini
Multiagent Connected Path Planning: PSPACE-Completeness and How to Deal With It. AAAI (2018)
Davide Tateo, Matteo Pirotta, Marcello Restelli, Andrea Bonarini
Gradient-based minimization for multi-expert Inverse Reinforcement Learning. SSCI (2017)
Davide Tateo, Carlo D'Eramo, Alessandro Nuara, Marcello Restelli, Andrea Bonarini
Exploiting structure and uncertainty of Bellman updates in Markov decision processes. SSCI (2017)