Shimon Whiteson

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Citations	10062	7889
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Jakob FoersterResearch Scientist, Facebook AI ResearchVerified email at fb.com
Gregory FarquharDeepMindVerified email at google.com
Frans A. OliehoekAssociate Professor at Delft University of TechnologyVerified email at tudelft.nl
Peter StoneProfessor of Computer Science, The University of Texas at AustinVerified email at cs.utexas.edu
Katja HofmannMicrosoft ResearchVerified email at microsoft.com
Diederik M. RoijersVrije Universiteit Brussel (VUB) & HU University of Applied Sciences UtrechtVerified email at ai.vub.ac.be
Christian Schroeder de WittUniversity of OxfordVerified email at robots.ox.ac.uk
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk
Tabish RashidUniversity of OxfordVerified email at cs.ox.ac.uk
Nantas NardelliPhD Student, University of OxfordVerified email at robots.ox.ac.uk
Wendelin BöhmerAlgorithmics Group, Delft University of TechnologyVerified email at tudelft.nl
Yannis AssaelResearch Scientist, Google DeepMindVerified email at google.com
Kyriacos ShiarlisWaymoVerified email at google.com
Matthijs T. J. SpaanDelft University of TechnologyVerified email at tudelft.nl
Nando de FreitasCIFAR & DeepMindVerified email at google.com
Maximilian IglUniversity of OxfordVerified email at eng.ox.ac.uk
Vitaly KurinMachine Learning PhD student at the University of Oxford, Whiteson Research labVerified email at cs.ox.ac.uk
Matthew E. TaylorAssociate Professor, University of AlbertaVerified email at ualberta.ca
Luisa M ZintgrafUniversity of OxfordVerified email at cs.ox.ac.uk
Tim RocktäschelAssociate Professor at University College London (UCL), Researcher at Facebook AI Research (FAIR)Verified email at cs.ucl.ac.uk

Shimon Whiteson

Professor of Computer Science, University of Oxford / Head of Research, Waymo UK

Verified email at cs.ox.ac.uk - Homepage

Artificial Intelligence Machine Learning Reinforcement Learning Decision-Theoretic Planning


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Learning to communicate with deep multi-agent reinforcement learning JN Foerster, YM Assael, N De Freitas, S Whiteson arXiv preprint arXiv:1605.06676, 2016	880	2016
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	790	2018
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	502	2018
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	418	2014
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	401	2017
Evolutionary Function Approximation for Reinforcement Learning S Whiteson, P Stone Journal of Machine Learning Research 7, 877-917, 2006	326	2006
Learning with opponent-learning awareness JN Foerster, RY Chen, M Al-Shedivat, S Whiteson, P Abbeel, I Mordatch arXiv preprint arXiv:1709.04326, 2017	307	2017
Lipnet: End-to-end sentence-level lipreading YM Assael, B Shillingford, S Whiteson, N De Freitas arXiv preprint arXiv:1611.01599, 2016	204	2016
Multiagent reinforcement learning for urban traffic control using coordination graphs L Kuyer, S Whiteson, B Bakker, N Vlassis Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008	202	2008
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	171	2009
The starcraft multi-agent challenge M Samvelyan, T Rashid, CS De Witt, G Farquhar, N Nardelli, TGJ Rudner, ... arXiv preprint arXiv:1902.04043, 2019	169	2019
Fast context adaptation via meta-learning L Zintgraf, K Shiarli, V Kurin, K Hofmann, S Whiteson International Conference on Machine Learning, 7693-7702, 2019	150	2019
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 (1), 63-90, 2013	136	2013
Exploiting locality of interaction in factored Dec-POMDPs FA Oliehoek, MTJ Spaan, N Vlassis, S Whiteson Int. Joint Conf. on Autonomous Agents and Multi-Agent Systems, 517-524, 2008	134	2008
Lipnet: Sentence-level lipreading YM Assael, B Shillingford, S Whiteson, N De Freitas arXiv preprint arXiv:1611.01599 2 (4), 2016	132	2016
Transfer via inter-task mappings in policy search reinforcement learning ME Taylor, S Whiteson, P Stone Proceedings of the 6th international joint conference on Autonomous agents …, 2007	131	2007
Deep variational reinforcement learning for POMDPs M Igl, L Zintgraf, TA Le, F Wood, S Whiteson International Conference on Machine Learning, 2117-2126, 2018	129	2018
Automatic feature selection in neuroevolution S Whiteson, P Stone, KO Stanley, R Miikkulainen, N Kohl Proceedings of the 7th annual conference on Genetic and evolutionary …, 2005	126	2005
Evolving soccer keepaway players through task decomposition S Whiteson, N Kohl, R Miikkulainen, P Stone Machine Learning 59 (1-2), 5-30, 2005	125	2005
A probabilistic method for inferring preferences from clicks K Hofmann, S Whiteson, M De Rijke Proceedings of the 20th ACM international conference on Information and …, 2011	123	2011

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