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Gregory Farquhar
Gregory Farquhar
DeepMind
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Title
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Cited by
Year
Counterfactual multi-agent policy gradients
J Foerster, G Farquhar, T Afouras, N Nardelli, S Whiteson
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
11762018
Qmix: Monotonic value function factorisation for deep multi-agent reinforcement learning
T Rashid, M Samvelyan, C Schroeder, G Farquhar, J Foerster, S Whiteson
International conference on machine learning, 4295-4304, 2018
9252018
Stabilising experience replay for deep multi-agent reinforcement learning
J Foerster, N Nardelli, G Farquhar, T Afouras, PHS Torr, P Kohli, ...
International conference on machine learning, 1146-1155, 2017
5132017
The starcraft multi-agent challenge
M Samvelyan, T Rashid, CS De Witt, G Farquhar, N Nardelli, TGJ Rudner, ...
arXiv preprint arXiv:1902.04043, 2019
3502019
A survey of reinforcement learning informed by natural language
J Luketina, N Nardelli, G Farquhar, J Foerster, J Andreas, E Grefenstette, ...
arXiv preprint arXiv:1906.03926, 2019
1362019
Treeqn and atreec: Differentiable tree-structured models for deep reinforcement learning
G Farquhar, T Rocktäschel, M Igl, S Whiteson
arXiv preprint arXiv:1710.11417, 2017
1122017
Weighted qmix: Expanding monotonic value function factorisation for deep multi-agent reinforcement learning
T Rashid, G Farquhar, B Peng, S Whiteson
Advances in neural information processing systems 33, 10199-10210, 2020
972020
Multi-agent common knowledge reinforcement learning
C Schroeder de Witt, J Foerster, G Farquhar, P Torr, W Boehmer, ...
Advances in Neural Information Processing Systems 32, 2019
71*2019
Dice: The infinitely differentiable monte carlo estimator
J Foerster, G Farquhar, M Al-Shedivat, T Rocktäschel, E Xing, S Whiteson
International Conference on Machine Learning, 1529-1538, 2018
632018
Transient non-stationarity and generalisation in deep reinforcement learning
M Igl, G Farquhar, J Luketina, W Boehmer, S Whiteson
arXiv preprint arXiv:2006.05826, 2020
232020
The impact of non-stationarity on generalisation in deep reinforcement learning
M Igl, G Farquhar, J Luketina, W Boehmer, S Whiteson
arXiv preprint arXiv:2006.05826, 2020
182020
Growing action spaces
G Farquhar, L Gustafson, Z Lin, S Whiteson, N Usunier, G Synnaeve
International Conference on Machine Learning, 3040-3051, 2020
162020
A baseline for any order gradient estimation in stochastic computation graphs
J Mao, J Foerster, T Rocktäschel, M Al-Shedivat, G Farquhar, S Whiteson
International Conference on Machine Learning, 4343-4351, 2019
102019
Counterfactual multi-agent policy gradients. CoRR abs/1705.08926 (2017)
JN Foerster, G Farquhar, T Afouras, N Nardelli, S Whiteson
arXiv preprint arXiv:1705.08926, 2017
92017
Proper value equivalence
C Grimm, A Barreto, G Farquhar, D Silver, S Singh
Advances in Neural Information Processing Systems 34, 7773-7786, 2021
62021
Loaded DiCE: Trading off bias and variance in any-order score function gradient estimators for reinforcement learning
G Farquhar, S Whiteson, J Foerster
Advances in Neural Information Processing Systems 32, 2019
52019
Psiphi-learning: Reinforcement learning with demonstrations using successor features and inverse temporal difference learning
A Filos, C Lyle, Y Gal, S Levine, N Jaques, G Farquhar
International Conference on Machine Learning, 3305-3317, 2021
42021
Self-consistent models and values
G Farquhar, K Baumli, Z Marinho, A Filos, M Hessel, HP van Hasselt, ...
Advances in Neural Information Processing Systems 34, 1111-1125, 2021
32021
No DICE: An Investigation of the Bias-Variance Tradeoff in Meta-Gradients
R Vuorio, JA Beck, G Farquhar, JN Foerster, S Whiteson
Deep RL Workshop NeurIPS 2021, 2021
22021
Multi-agent common knowledge reinforcement learning
CA Schroeder, J Foerster, G Farquhar, P Torr, W Boehmer, S Whiteson
12019
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