| A practical guide to multi-objective reinforcement learning and planning CF Hayes, R Rădulescu, E Bargiacchi, J Källström, M Macfarlane, ... Autonomous Agents and Multi-Agent Systems 36 (1), 26, 2022 | 265 | 2022 |
| Pareto-DQN: Approximating the Pareto front in complex multi-objective decision problems M Reymond, A Nowé Proceedings of the adaptive and learning agents workshop (ALA-19) at AAMAS, 2019 | 34 | 2019 |
| Distributional monte carlo tree search for risk-aware and multi-objective reinforcement learning CF Hayes, M Reymond, DM Roijers, E Howley, P Mannion Proceedings of the 20th international conference on autonomous agents and …, 2021 | 24 | 2021 |
| Actor-critic multi-objective reinforcement learning for non-linear utility functions M Reymond, CF Hayes, D Steckelmacher, DM Roijers, A Nowé Autonomous Agents and Multi-Agent Systems 37 (2), 23, 2023 | 22 | 2023 |
| Pareto conditioned networks M Reymond, E Bargiacchi, A Nowé arXiv preprint arXiv:2204.05036, 2022 | 22 | 2022 |
| Risk aware and multi-objective decision making with distributional monte carlo tree search CF Hayes, M Reymond, DM Roijers, E Howley, P Mannion arXiv preprint arXiv:2102.00966, 2021 | 17 | 2021 |
| Reinforcement learning for demand response of domestic household appliances C Patyn, M Reymond, R Rădulescu, G Deconinck, A Nowé Adaptive Learning Agents 2018 Proceedings, 1-7, 2018 | 15 | 2018 |
| Local advantage networks for cooperative multi-agent reinforcement learning R Avalos, M Reymond, A Nowé, DM Roijers arXiv preprint arXiv:2112.12458, 2021 | 12 | 2021 |
| Interactive multi-objective reinforcement learning in multi-armed bandits with gaussian process utility models DM Roijers, LM Zintgraf, P Libin, M Reymond, E Bargiacchi, A Nowé Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021 | 11 | 2021 |
| Exploring the pareto front of multi-objective covid-19 mitigation policies using reinforcement learning M Reymond, CF Hayes, L Willem, R Rădulescu, S Abrams, DM Roijers, ... Expert Systems with Applications 249, 123686, 2024 | 8 | 2024 |
| Monte Carlo tree search algorithms for risk-aware and multi-objective reinforcement learning CF Hayes, M Reymond, DM Roijers, E Howley, P Mannion Autonomous Agents and Multi-Agent Systems 37 (2), 26, 2023 | 7 | 2023 |
| Near on-policy experience sampling in multi-objective reinforcement learning S Wang, M Reymond, AA Irissappane, DM Roijers Proceedings of the 21st International Conference on Autonomous Agents and …, 2022 | 4 | 2022 |
| WAE-PCN: Wasserstein-autoencoded Pareto Conditioned Networks F Delgrange, M Reymond, A Nowé, GA Pérez 2023 adaptive and learning agents workshop at AAMAS, 1-7, 2023 | 2 | 2023 |
| Local advantage networks for multi-agent reinforcement learning in dec-pomdps R Avalos, M Reymond, A Nowe, DM Roijers Proc. of the Adaptive and Learning Agents Workshop (ALA 2023), https://ewrl …, 2022 | 2 | 2022 |
| A Brief Guide to Multi-Objective Reinforcement Learning and Planning CF Hayes, R Rădulescu, E Bargiacchi, J Kallstrom, M Macfarlane, ... Proceedings of the 2023 International Conference on Autonomous Agents and …, 2023 | 1 | 2023 |
| Interactively Learning the User's Utility for Best-Arm Identification in Multi-Objective Multi-Armed Bandits M Reymond, E Bargiacchi, DM Roijers, A Nowé Proceedings of the 23rd International Conference on Autonomous Agents and …, 2024 | | 2024 |
| Divide and Conquer: Provably Unveiling the Pareto Front with Multi-Objective Reinforcement Learning W Röpke, M Reymond, P Mannion, DM Roijers, A Nowé, R Rădulescu arXiv preprint arXiv:2402.07182, 2024 | | 2024 |
| On incorporating prior knowledge about the decision maker in multi-objective reinforcement learning M Reymond Vrije Universiteit Brussel, 2023 | | 2023 |
| Hybrid AI for Visual Question Answering on CLEVR J Nevens, R Radulescu, M Reymond, P Van Eecke, K Efthymiadis, ... 30th Benelux Conference on Artificial Intelligence, 171-172, 2018 | | 2018 |
