| Optimal model-free output synchronization of heterogeneous systems using off-policy reinforcement learning H Modares, SP Nageshrao, GAD Lopes, R Babuška, FL Lewis Automatica 71, 334-341, 2016 | 114 | 2016 |
| Autonomous highway driving using deep reinforcement learning S Nageshrao, HE Tseng, D Filev 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC …, 2019 | 59 | 2019 |
| Port-hamiltonian systems in adaptive and learning control: A survey SP Nageshrao, GAD Lopes, D Jeltsema, R Babuška IEEE Transactions on Automatic Control 61 (5), 1223-1238, 2015 | 58 | 2015 |
| Reinforcement learning based compensation methods for robot manipulators YP Pane, SP Nageshrao, J Kober, R Babuška Engineering Applications of Artificial Intelligence 78, 236-247, 2019 | 48 | 2019 |
| Reinforcement learning for port-Hamiltonian systems O Sprangers, R Babuška, SP Nageshrao, GAD Lopes IEEE transactions on cybernetics 45 (5), 1017-1027, 2014 | 40 | 2014 |
| Passivity-based reinforcement learning control of a 2-DOF manipulator arm SP Nageshrao, GAD Lopes, D Jeltsema, R Babuška Mechatronics 24 (8), 1001-1007, 2014 | 29 | 2014 |
| Actor-critic reinforcement learning for tracking control in robotics YP Pane, SP Nageshrao, R Babuška 2016 IEEE 55th conference on decision and control (CDC), 5819-5826, 2016 | 23 | 2016 |
| Deep reinforcement learning with enhanced safety for autonomous highway driving A Baheri, S Nageshrao, HE Tseng, I Kolmanovsky, A Girard, D Filev 2020 IEEE Intelligent Vehicles Symposium (IV), 1550-1555, 2020 | 20 | 2020 |
| Learning complex behaviors via sequential composition and passivity-based control GAD Lopes, E Najafi, SP Nageshrao, R Babuška Handling Uncertainty and Networked Structure in Robot Control, 53-74, 2015 | 15 | 2015 |
| Explaining deep learning models through rule-based approximation and visualization E Soares, PP Angelov, B Costa, MPG Castro, S Nageshrao, D Filev IEEE Transactions on Fuzzy Systems 29 (8), 2399-2407, 2020 | 14 | 2020 |
| Charging cost optimization for EV buses using neural network based energy predictor SP Nageshrao, J Jacob, S Wilkins IFAC-PapersOnLine 50 (1), 5947-5952, 2017 | 13 | 2017 |
| Rapid learning in sequential composition control E Najafi, GAD Lopes, SP Nageshrao, R Babuška 53rd IEEE Conference on Decision and Control, 5171-5176, 2014 | 13 | 2014 |
| Interpretable approximation of a deep reinforcement learning agent as a set of if-then rules S Nageshrao, B Costa, D Filev 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 10 | 2019 |
| Discretionary lane change decision making using reinforcement learning with model-based exploration S Zhang, H Peng, S Nageshrao, E Tseng 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 8 | 2019 |
| Explainable density-based approach for self-driving actions classification E Soares, P Angelov, D Filev, B Costa, M Castro, S Nageshrao 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 8 | 2019 |
| Interconnection and damping assignment control via reinforcement learning SP Nageshrao, GAD Lopes, D Jeltsema, R Babuška IFAC Proceedings Volumes 47 (3), 1760-1765, 2014 | 7 | 2014 |
| A Convex Programming Approach to Data-Driven Risk-Averse Reinforcement Learning Y Han, M Mazouchi, S Nageshrao, H Modares arXiv preprint arXiv:2103.14606, 2021 | 4 | 2021 |
| Interpretable-AI Policies using Evolutionary Nonlinear Decision Trees for Discrete Action Systems Y Dhebar, K Deb, S Nageshrao, L Zhu, D Filev arXiv preprint arXiv:2009.09521, 2020 | 4 | 2020 |
| Vehicle adaptive learning S Nageshrao, HE Tseng, DP Filev, RL Baker, C Cruise, L Daehler, ... US Patent 10,733,510, 2020 | 4 | 2020 |
| An online evolving framework for advancing reinforcement-learning based automated vehicle control T Han, S Nageshrao, DP Filev, Ü Özgüner IFAC-PapersOnLine 53 (2), 8118-8123, 2020 | 4 | 2020 |
Robert BabuskaProfessor, Delft University of Technology, Czech Technical University PragueVerified email at tudelft.nl
