Virtual-to-real deep reinforcement learning: Continuous control of mobile robots for mapless navigation L Tai, G Paolo, M Liu 2017 IEEE/RSJ international conference on intelligent robots and systems …, 2017 | 850 | 2017 |
A data-driven model for interaction-aware pedestrian motion prediction in object cluttered environments M Pfeiffer, G Paolo, H Sommer, J Nieto, R Siegwart, C Cadena 2018 IEEE International Conference on Robotics and Automation (ICRA), 5921-5928, 2018 | 129 | 2018 |
Unsupervised Learning and Exploration of Reachable Outcome Space G Paolo, A Laflaquière, A Coninx, S Doncieux 2020 IEEE International Conference on Robotics and Automation, ICRA 2020, 2019 | 30 | 2019 |
Novelty search makes evolvability inevitable S Doncieux, G Paolo, A Laflaquière, A Coninx Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 85-93, 2020 | 26 | 2020 |
Sparse reward exploration via novelty search and emitters G Paolo, A Coninx, S Doncieux, A Laflaquière Proceedings of the 2021 Genetic and Evolutionary Computation Conference, 2021 | 19 | 2021 |
Towards continuous control of flippers for a multi-terrain robot using deep reinforcement learning G Paolo, L Tai, M Liu arXiv preprint arXiv:1709.08430, 2017 | 10 | 2017 |
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention R Ilbert, A Odonnat, V Feofanov, A Virmaux, G Paolo, T Palpanas, I Redko Forty-first International Conference on Machine Learning, 0 | 5* | |
Guided safe shooting: model based reinforcement learning with safety constraints G Paolo, J Gonzalez-Billandon, A Thomas, B Kégl arXiv preprint arXiv:2206.09743, 2022 | 3 | 2022 |
Discovering and Exploiting Sparse Rewards in a Learned Behavior Space G Paolo, M Coninx, A Laflaquière, S Doncieux Evolutionary Computation, 1-31, 2024 | 2 | 2024 |
Learning in Sparse Rewards settings through Quality-Diversity algorithms G Paolo arXiv preprint arXiv:2203.01027, 2022 | 2 | 2022 |
Position: A Call for Embodied AI G Paolo, J Gonzalez-Billandon, B Kégl Forty-first International Conference on Machine Learning, 0 | 1* | |
A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning A Benechehab, A Thomas, G Paolo, M Filippone, B Kégl arXiv preprint arXiv:2402.03146, 2024 | | 2024 |
Multi-timestep models for Model-based Reinforcement Learning A Benechehab, G Paolo, A Thomas, M Filippone, B Kégl arXiv preprint arXiv:2310.05672, 2023 | | 2023 |
Editorial to the “Evolutionary Reinforcement Learning” Special Issue A Gaier, G Paolo, A Cully ACM Transactions on Evolutionary Learning 3 (3), 1-2, 2023 | | 2023 |
A Study of the Weighted Multi-step Loss Impact on the Predictive Error and the Return in MBRL A Benechehab, A Thomas, G Paolo, M Filippone, B Kégl I Can't Believe It's Not Better Workshop: Failure Modes of Sequential …, 0 | | |
Fair Model-Based Reinforcement Learning Comparisons with Explicit and Consistent Update Frequency A Thomas, A Benechehab, G Paolo, B Kégl The Third Blogpost Track at ICLR 2024, 0 | | |