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Lukas Schäfer
Lukas Schäfer
Microsoft Research Cambridge
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Benchmarking multi-agent deep reinforcement learning algorithms in cooperative tasks
G Papoudakis, F Christianos, L Schäfer, SV Albrecht
Conference on Neural Information Processing Systems, Track on Datasets and …, 2020
332*2020
Shared experience actor-critic for multi-agent reinforcement learning
F Christianos, L Schäfer, S Albrecht
Advances in neural information processing systems 33, 10707-10717, 2020
2042020
Multi-agent reinforcement learning: Foundations and modern approaches
SV Albrecht, F Christianos, L Schäfer
Massachusetts Institute of Technology: Cambridge, MA, USA, 2024
1342024
Decoupled reinforcement learning to stabilise intrinsically-motivated exploration
L Schäfer, F Christianos, JP Hanna, SV Albrecht
Proceedings of the 21st International Conference on Autonomous Agents and …, 2022
44*2022
Scalable multi-agent reinforcement learning for warehouse logistics with robotic and human co-workers
A Krnjaic, RD Steleac, JD Thomas, G Papoudakis, L Schäfer, AWK To, ...
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2024
242024
Robust on-policy sampling for data-efficient policy evaluation in reinforcement learning
R Zhong, D Zhang, L Schäfer, S Albrecht, J Hanna
Advances in Neural Information Processing Systems 35, 37376-37388, 2022
16*2022
Deep reinforcement learning for multi-agent interaction
IH Ahmed, C Brewitt, I Carlucho, F Christianos, M Dunion, E Fosong, ...
Ai Communications 35 (4), 357-368, 2022
162022
Curiosity in Multi-Agent Reinforcement Learning
L Schäfer
University of Edinburgh, 2019
82019
Learning task embeddings for teamwork adaptation in multi-agent reinforcement learning
L Schäfer, F Christianos, A Storkey, SV Albrecht
arXiv preprint arXiv:2207.02249, 2022
72022
Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning
L Schäfer, O Slumbers, S McAleer, Y Du, SV Albrecht, D Mguni
Adaptive and Learning Agents Workshop, AAMAS 2023, 2023
62023
Learning temporally-consistent representations for data-efficient reinforcement learning
T McInroe, L Schäfer, SV Albrecht
arXiv preprint arXiv:2110.04935, 2021
52021
Visual encoders for data-efficient imitation learning in modern video games
L Schäfer, L Jones, A Kanervisto, Y Cao, T Rashid, R Georgescu, ...
arXiv preprint arXiv:2312.02312, 2023
32023
Using Offline Data to Speed-up Reinforcement Learning in Procedurally Generated Environments
A Andres, L Schäfer, E Villar-Rodriguez, SV Albrecht, J Del Ser
Adaptive and Learning Agents Workshop, AAMAS 2023, 2023
32023
Task generalisation in multi-agent reinforcement learning
L Schäfer
Proceedings of the 21st International Conference on Autonomous Agents and …, 2022
32022
Learning Representations for Reinforcement Learning with Hierarchical Forward Models
T McInroe, L Schäfer, SV Albrecht
Deep Reinforcement Learning Workshop NeurIPS 2022, 0
2*
Domain-Dependent Policy Learning using Neural Networks in Classical Planning
L Schäfer
Saarland University, 2018
12018
Multi-Horizon Representations with Hierarchical Forward Models for Reinforcement Learning
T McInroe, L Schäfer, SV Albrecht
Transactions on Machine Learning Research, 0
1
Efficient exploration in single-agent and multi-agent deep reinforcement learning
L Schäfer
The University of Edinburgh, 2024
2024
Autonomous Agents Research Group
S Albrecht, F Christianos, L Schäfer, A Kuznietsov, B Gyevnar, C Wang, ...
2020
The UK Multi-Agent Systems Symposium
L Schäfer
2020
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