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Shimon Whiteson
Shimon Whiteson
Professor of Computer Science, University of Oxford / Senior Staff Research Scientist, Waymo
Verified email at cs.ox.ac.uk - Homepage
Title
Cited by
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
18262018
Monotonic value function factorisation for deep multi-agent reinforcement learning
T Rashid, M Samvelyan, CS De Witt, G Farquhar, J Foerster, S Whiteson
The Journal of Machine Learning Research 21 (1), 7234-7284, 2020
18092020
Learning to communicate with deep multi-agent reinforcement learning
J Foerster, IA Assael, N De Freitas, S Whiteson
Advances in neural information processing systems 29, 2016
17722016
The starcraft multi-agent challenge
M Samvelyan, T Rashid, CS De Witt, G Farquhar, N Nardelli, TGJ Rudner, ...
arXiv preprint arXiv:1902.04043, 2019
7462019
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
6712017
A survey of multi-objective sequential decision-making
DM Roijers, P Vamplew, S Whiteson, R Dazeley
Journal of Artificial Intelligence Research 48, 67-113, 2014
6502014
Learning with opponent-learning awareness
JN Foerster, RY Chen, M Al-Shedivat, S Whiteson, P Abbeel, I Mordatch
arXiv preprint arXiv:1709.04326, 2017
5322017
Lipnet: End-to-end sentence-level lipreading
YM Assael, B Shillingford, S Whiteson, N De Freitas
arXiv preprint arXiv:1611.01599, 2016
3952016
Fast context adaptation via meta-learning
L Zintgraf, K Shiarli, V Kurin, K Hofmann, S Whiteson
International Conference on Machine Learning, 7693-7702, 2019
3612019
Evolutionary Function Approximation for Reinforcement Learning
S Whiteson, P Stone
Journal of Machine Learning Research 7, 877-917, 2006
3562006
Maven: Multi-agent variational exploration
A Mahajan, T Rashid, M Samvelyan, S Whiteson
Advances in neural information processing systems 32, 2019
3182019
Multiagent reinforcement learning for urban traffic control using coordination graphs
L Kuyer, S Whiteson, B Bakker, N Vlassis
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2008
2932008
Deep variational reinforcement learning for POMDPs
M Igl, L Zintgraf, TA Le, F Wood, S Whiteson
International Conference on Machine Learning, 2117-2126, 2018
2712018
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
2542019
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
2522020
A theoretical and empirical analysis of Expected Sarsa
H Van Seijen, H Van Hasselt, S Whiteson, M Wiering
2009 ieee symposium on adaptive dynamic programming and reinforcement …, 2009
2522009
Varibad: A very good method for bayes-adaptive deep rl via meta-learning
L Zintgraf, K Shiarlis, M Igl, S Schulze, Y Gal, K Hofmann, S Whiteson
arXiv preprint arXiv:1910.08348, 2019
2062019
Lipnet: Sentence-level lipreading
YM Assael, B Shillingford, S Whiteson, N De Freitas
arXiv preprint arXiv:1611.01599 2 (4), 2016
1702016
Balancing exploration and exploitation in listwise and pairwise online learning to rank for information retrieval
K Hofmann, S Whiteson, M de Rijke
Information Retrieval 16, 63-90, 2013
1612013
Learning to communicate to solve riddles with deep distributed recurrent q-networks
JN Foerster, YM Assael, N de Freitas, S Whiteson
arXiv preprint arXiv:1602.02672, 2016
1592016
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