Shimon Whiteson - Google Scholar

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	All	Since 2015
Citations	7153	5462
h-index	46	38
i10-index	108	93

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Co-authors

Jakob FoersterResearch Scientist, Facebook AI ResearchVerified email at fb.com
Peter StoneProfessor of Computer Science, The University of Texas at AustinVerified email at cs.utexas.edu
Gregory FarquharUniversity of OxfordVerified email at cs.ox.ac.uk
Frans A. OliehoekAssociate Professor at Delft University of TechnologyVerified email at tudelft.nl
Diederik M. RoijersVrije Universiteit Brussel (VUB) & HU University of Applied Sciences UtrechtVerified email at ai.vub.ac.be
Katja HofmannMicrosoft ResearchVerified email at microsoft.com
Matthijs T. J. SpaanDelft University of TechnologyVerified email at tudelft.nl
Nantas NardelliPhD Student, University of OxfordVerified email at robots.ox.ac.uk
Yannis AssaelResearch Scientist, Google DeepMindVerified email at google.com
Nando de FreitasCIFAR & DeepMindVerified email at google.com
Kyriacos ShiarlisWaymoVerified email at google.com
Matthew E. TaylorAssociate Professor, University of AlbertaVerified email at ualberta.ca
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
Anne SchuthHead of News Personalisation, DPG Media, The NetherlandsVerified email at dpgmedia.nl
Tim RocktäschelResearch Scientist at Facebook AI Research, Lecturer at University College LondonVerified email at cs.ucl.ac.uk
Wendelin BöhmerWhiteson Research Lab, University of OxfordVerified email at cs.ox.ac.uk
Maximilian IglUniversity of OxfordVerified email at eng.ox.ac.uk
Guangliang LiAssistant Professor, Department of Electronic Engineering, Ocean University of China, Qingdao, ChinaVerified email at ouc.edu.cn

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 J Foerster, IA Assael, N De Freitas, S Whiteson Advances in neural information processing systems, 2137-2145, 2016	586	2016
Counterfactual multi-agent policy gradients J Foerster, G Farquhar, T Afouras, N Nardelli, S Whiteson arXiv preprint arXiv:1705.08926, 2017	446	2017
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	320	2014
Evolutionary Function Approximation for Reinforcement Learning S Whiteson, P Stone Journal of Machine Learning Research 7, 877-917, 2006	306	2006
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	256	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	213	2018
Learning with opponent-learning awareness JN Foerster, RY Chen, M Al-Shedivat, S Whiteson, P Abbeel, I Mordatch arXiv preprint arXiv:1709.04326, 2017	195	2017
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	166	2008
Lipnet: End-to-end sentence-level lipreading YM Assael, B Shillingford, S Whiteson, N De Freitas arXiv preprint arXiv:1611.01599, 2016	133	2016
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	126	2009
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	124	2007
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	122	2013
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	122	2005
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	120	2008
Comparing evolutionary and temporal difference methods in a reinforcement learning domain ME Taylor, S Whiteson, P Stone Proceedings of the 8th annual conference on Genetic and evolutionary …, 2006	117	2006
Evolving soccer keepaway players through task decomposition S Whiteson, N Kohl, R Miikkulainen, P Stone Machine Learning 59 (1-2), 5-30, 2005	116	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	110	2011
Adaptive tile coding for value function approximation S Whiteson	106	2007
Lipnet: Sentence-level lipreading YM Assael, B Shillingford, S Whiteson, N de Freitas arXiv preprint arXiv:1611.01599 2 (8), 2016	101	2016
Reusing historical interaction data for faster online learning to rank for IR K Hofmann, A Schuth, S Whiteson, M De Rijke Proceedings of the sixth ACM international conference on Web search and data …, 2013	90	2013

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