| Model-based reinforcement learning: A survey TM Moerland, J Broekens, A Plaat, CM Jonker Foundations and Trends® in Machine Learning, 2023 | 971 | 2023 |
| Emotion in Reinforcement Learning Agents and Robots: A Survey TM Moerland, J Broekens, CM Jonker Machine Learning, https://doi.org/10.1007/s10994-017-5666, 2017 | 204 | 2017 |
| A0C: Alpha Zero in Continuous Action Space TM Moerland, J Broekens, A Plaat, CM Jonker Planning and Learning Workshop at the 35th International Conference on …, 2018 | 71 | 2018 |
| Efficient exploration with Double Uncertain Value Networks TM Moerland, J Broekens, CM Jonker Deep Reinforcement Learning Symposium at the 30th Conference on Advances in …, 2017 | 60 | 2017 |
| A unifying framework for reinforcement learning and planning TM Moerland, J Broekens, A Plaat, CM Jonker Frontiers in Artificial Intelligence 5, 908353, 2022 | 51 | 2022 |
| Learning Multimodal Transition Dynamics for Model-Based Reinforcement Learning TM Moerland, J Broekens, CM Jonker Scaling Up Reinforcement Learning (SURL) workshop @ European Conference on …, 2017 | 44 | 2017 |
| RRT-CoLearn: towards kinodynamic planning without numerical trajectory optimization WJ Wolfslag, M Bharatheesha, TM Moerland, M Wisse IEEE Conference on Robotics and Automation (ICRA), 2018 | 40 | 2018 |
| Fear and Hope Emerge from Anticipation in Model-Based Reinforcement Learning. TM Moerland, J Broekens, CM Jonker Proceedings of the 25th International Joint Conference on Artificial …, 2016 | 27 | 2016 |
| Monte Carlo Tree Search for Asymmetric Trees TM Moerland, J Broekens, A Plaat, CM Jonker Planning and Learning Workshop at the 35th International Conference on …, 2018 | 22* | 2018 |
| Think Too Fast Nor Too Slow: The Computational Trade-off Between Planning And Reinforcement Learning TM Moerland, A Deichler, S Baldi, J Broekens, CM Jonker Bridging the Gap Between AI Planning and Reinforcement Learning (PRL …, 2020 | 13* | 2020 |
| The Potential of the Return Distribution for Exploration in RL TM Moerland, J Broekens, CM Jonker Exploration in Reinforcement Learning Workshop at the 35th International …, 2018 | 13 | 2018 |
| Are LSTMs good few-shot learners? M Huisman, TM Moerland, A Plaat, JN van Rijn Machine Learning 112 (11), 4635-4662, 2023 | 11 | 2023 |
| Visualizing MuZero Models JA de Vries, KS Voskuil, TM Moerland, A Plaat Workshop on Unsupervised Reinforcement Learning, ICML, 2021 | 11 | 2021 |
| Tutored learning: an effective way for students to benefit research by critical appraisal VT Janmaat, KE Kortekaas, TM Moerland, MWC Vereijken, JW Schoones, ... Medical Science Educator 23, 269-277, 2013 | 11 | 2013 |
| Continuous Markov decision process and policy search T Moerland Lecture notes for the course reinforcement learning, Leiden University 28 …, 2021 | 4 | 2021 |
| Two-memory reinforcement learning Z Yang, TM Moerland, M Preuss, A Plaat 2023 IEEE Conference on Games (CoG), 1-9, 2023 | 3 | 2023 |
| Continuous episodic control Z Yang, TM Moerland, M Preuss, A Plaat 2023 IEEE Conference on Games (CoG), 1-8, 2023 | 3 | 2023 |
| The Intersection of Planning and Learning TM Moerland PhD thesis, Delft University of Technology, 2021 | 3 | 2021 |
| First go, then post-explore: the benefits of post-exploration in intrinsic motivation Z Yang, TM Moerland, M Preuss, A Plaat arXiv preprint arXiv:2212.03251, 2022 | 2 | 2022 |
| Knowing What You Don’t Know - Novelty Detection for Action Recognition in Personal Robots T Moerland, A Chandarr, M Rudinac, P Jonker Proceedings of the 11th Joint Conference on Computer Vision, Imaging and …, 2016 | 2 | 2016 |
