Frans A. Oliehoek

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Matthijs T. J. SpaanDelft University of TechnologyVerified email at tudelft.nl
Christopher AmatoAssistant Professor at Northeastern UniversityVerified email at ccs.neu.edu
Shimon WhitesonProfessor of Computer Science, University of Oxford / Head of Research, Waymo UKVerified email at cs.ox.ac.uk
Nikos VlassisPrincipal Scientist, AdobeVerified email at adobe.com
Diederik M. RoijersVrije Universiteit Brussel (VUB) & HU University of Applied Sciences UtrechtVerified email at ai.vub.ac.be
Elise van der PolMicrosoft ResearchVerified email at microsoft.com
Karl TuylsResearch Scientist, Google DeepMind and Professor of computer science, University of LiverpoolVerified email at google.com
Stefan WitwickiAlliance Innovation Lab Silicon ValleyVerified email at nissan-usa.com
Jie ZhangAssociate Professor, Computer Science and Engineering, NTU, SingaporeVerified email at ntu.edu.sg
Rahul SavaniProfessor of Computer Science, University of LiverpoolVerified email at liverpool.ac.uk
Sammie KattNortheastern UniversityVerified email at husky.neu.edu
Mathijs de WeerdtAssociate Professor of Computer Science, Delft University of TechnologyVerified email at tudelft.nl
Joris ScharpffDelft University of TechnologyVerified email at tudelft.nl
Leslie KaelblingVerified email at csail.mit.edu
Athirai A. IrissappaneVerified email at uw.edu
João MessiasLatent LogicVerified email at latentlogic.com
Miguel SuauDelft University of TechnologyVerified email at tudelft.nl
Elena CongedutiDelft University of TechnologyVerified email at tudelft.nl
Max WellingProfessor Machine Learning, University of AmsterdamVerified email at uva.nl
Rolf A. N. StarreDelft University of TechnologyVerified email at tudelft.nl

Frans A. Oliehoek

Associate Professor at Delft University of Technology

Verified email at tudelft.nl - Homepage

artificial intelligence multiagent systems machine learning reinforcement learning decision-theoretic planning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A Concise Introduction to Decentralized POMDPs FA Oliehoek, C Amato	432	2016
Optimal and approximate Q-value functions for decentralized POMDPs FA Oliehoek, MTJ Spaan, N Vlassis Journal of Artificial Intelligence Research 32 (1), 289-353, 2008	321	2008
Coordinated Deep Reinforcement Learners for Traffic Light Control E van der Pol, FA Oliehoek NIPS WS: Learning, Inference and Control of Multi-Agent Systems, 2016	250	2016
Exploiting locality of interaction in factored Dec-POMDPs FA Oliehoek, MTJ Spaan, S Whiteson, N Vlassis Proceedings of the 7th international conference on Autonomous agents and …, 2008	137	2008
Decentralized POMDPs FA Oliehoek Reinforcement Learning: State of the Art, 2012	119	2012
Scalable Planning and Learning for Multiagent POMDPs: Extended Version C Amato, FA Oliehoek arXiv preprint arXiv:1404.1140, 2014	94*	2014
Approximate Solutions for Factored Dec-POMDPs with Many Agents---Extended Abstract F Oliehoek, S Whiteson, M Spaan BNAIC 2013: Proceedings of the Twenty-Fifth Benelux Conference on Artificial …, 2013	79*	2013
Approximate Solutions for Factored Dec-POMDPs with Many Agents FA Oliehoek, S Whiteson, MTJ Spaan Proceedings of the Twelfth International Joint Conference on Autonomous …, 2013	79	2013
Decentralised Online Planning for Multi-Robot Warehouse Commissioning D Claes, F Oliehoek, H Baier, K Tuyls Proceedings of the 16th Conference on Autonomous Agents and MultiAgent …, 2017	64	2017
Incremental Clustering and Expansion for Faster Optimal Planning in Decentralized POMDPs. FA Oliehoek, MTJ Spaan, C Amato, S Whiteson Journal of Artificial Intelligence Research 46 (1), 2013	63	2013
A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence Z Akata, D Balliet, M de Rijke, F Dignum, V Dignum, G Eiben, A Fokkens, ... Computer 53 (8), 18-28, 2020	60	2020
Scaling up optimal heuristic search in Dec-POMDPs via incremental expansion MTJ Spaan, FA Oliehoek, C Amato Proceedings of the Twenty-Second international joint conference on …, 2011	59	2011
Scaling up optimal heuristic search in Dec-POMDPs via incremental expansion MTJ Spaan, FA Oliehoek, C Amato Multi-agent Sequential Decision Making in Uncertain Domains, 2011	59	2011
Influence-Based Abstraction for Multiagent Systems FA Oliehoek, SJ Witwicki, LP Kaelbling Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence …, 2012	53	2012
Learning in POMDPs with Monte Carlo Tree Search S Katt, FA Oliehoek, C Amato International Conference on Machine Learning, 1819-1827, 2017	51	2017
Lossless clustering of histories in decentralized POMDPs FA Oliehoek, S Whiteson, MTJ Spaan Proceedings of The 8th International Conference on Autonomous Agents and …, 2009	50	2009
Multiagent planning under uncertainty with stochastic communication delays MTJ Spaan, FA Oliehoek, N Vlassis Proc. of The International Conference on Automated Planning and Scheduling …, 2008	50	2008
Maximizing the Probability of Arriving on Time: A Practical Q-Learning Method Z Cao, H Guo, J Zhang, F Oliehoek, U Fastenrath Proceedings of the 31th AAAI Conference on Artificial Intelligence (AAAI), 2017	49	2017
The cross-entropy method for policy search in decentralized POMDPs FA Oliehoek, JFP Kooij, N Vlassis Informatica 32 (4), 341-357, 2008	48	2008
Value-based Planning for Teams of Agents in Stochastic Partially Observable Environments FA Oliehoek Informatics Institute, University of Amsterdam, 2010	47	2010

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