Dealing with non-stationarity in multi-agent deep reinforcement learning G Papoudakis, F Christianos, A Rahman, SV Albrecht arXiv preprint arXiv:1906.04737, 2019 | 154 | 2019 |
Benchmarking multi-agent deep reinforcement learning algorithms in cooperative tasks G Papoudakis, F Christianos, L Schäfer, SV Albrecht Neural Information Processing Systems Track on Datasets and Benchmarks, 2021 | 129* | 2021 |
Agent modelling under partial observability for deep reinforcement learning G Papoudakis, F Christianos, S Albrecht Advances in Neural Information Processing Systems 34, 19210-19222, 2021 | 52* | 2021 |
Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing F Christianos, G Papoudakis, A Rahman, SV Albrecht International Conference on Machine Learning, 2021 | 52 | 2021 |
Deep reinforcement learning for Doom using unsupervised auxiliary tasks G Papoudakis, KC Chatzidimitriou, PA Mitkas arXiv preprint arXiv:1807.01960, 2018 | 11 | 2018 |
Deep reinforcement learning for multi-agent interaction IH Ahmed, C Brewitt, I Carlucho, F Christianos, M Dunion, E Fosong, ... AI Communications, 1-12, 2022 | 5 | 2022 |
Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers A Krnjaic, JD Thomas, G Papoudakis, L Schäfer, P Börsting, SV Albrecht arXiv preprint arXiv:2212.11498, 2022 | 2 | 2022 |
Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning F Christianos, G Papoudakis, SV Albrecht arXiv preprint arXiv:2209.14344, 2022 | 1 | 2022 |
A generative model for sparse, evolving digraphs G Papoudakis, P Preux, M Monperrus Complex Networks & Their Applications VI: Proceedings of Complex Networks …, 2018 | | 2018 |