Gregory Farquhar
Gregory Farquhar
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Counterfactual multi-agent policy gradients
JN Foerster, G Farquhar, T Afouras, N Nardelli, S Whiteson
Thirty-second AAAI conference on artificial intelligence, 2018
Stabilising experience replay for deep multi-agent reinforcement learning
J Foerster, N Nardelli, G Farquhar, T Afouras, PHS Torr, P Kohli, ...
arXiv preprint arXiv:1702.08887, 2017
QMIX: Monotonic value function factorisation for deep multi-agent reinforcement learning
T Rashid, M Samvelyan, CS De Witt, G Farquhar, J Foerster, S Whiteson
arXiv preprint arXiv:1803.11485, 2018
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
The starcraft multi-agent challenge
M Samvelyan, T Rashid, CS de Witt, G Farquhar, N Nardelli, TGJ Rudner, ...
arXiv preprint arXiv:1902.04043, 2019
Dice: The infinitely differentiable monte-carlo estimator
J Foerster, G Farquhar, M Al-Shedivat, T Rocktäschel, EP Xing, ...
arXiv preprint arXiv:1802.05098, 2018
Multi-agent common knowledge reinforcement learning
CS de Witt, J Foerster, G Farquhar, P Torr, W Boehmer, S Whiteson
Advances in Neural Information Processing Systems, 9927-9939, 2019
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
Convergence rates of distributed TD (0) with linear function approximation for multi-agent reinforcement learning
TT Doan, ST Maguluri, J Romberg
arXiv preprint arXiv:1902.07393, 2019
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
A baseline for any order gradient estimation in stochastic computation graphs
J Mao, J Foerster, T Rocktaschel, M Al-Shedivat, G Farquhar, S Whiteson
Journal of Machine Learning Research, 2019
Multi-agent common knowledge reinforcement learning
CA Schroeder de Witt, JN Foerster, G Farquhar, PHS Torr, W Boehmer, ...
arXiv, arXiv: 1810.11702, 2018
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
Growing action spaces
G Farquhar, L Gustafson, Z Lin, S Whiteson, N Usunier, G Synnaeve
arXiv preprint arXiv:1906.12266, 2019
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, 8151-8162, 2019
Weighted QMIX: Expanding Monotonic Value Function Factorisation
T Rashid, G Farquhar, B Peng, S Whiteson
arXiv preprint arXiv:2006.10800, 2020
The StarCraft Multi-Agent Challenge
T Rashid, PHS Torr, G Farquhar, CM Hung, TGJ Rudner, N Nardelli, ...
International Foundation for Autonomous Agents and Multiagent Systems, 2019
論文 1–17