Daniel Hennes

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	Visi	Nuo 2018
Šaltiniai	1985	1580
h-rodyklė	23	20
i10-rodyklė	43	33

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Karl TuylsResearch Scientist, Google DeepMind and Professor of computer science, University of LiverpoolPatvirtintas el. paštas google.com
Dario IzzoScientist at the European Space AgencyPatvirtintas el. paštas esa.int
Daan BloembergenAI Researcher, City of AmsterdamPatvirtintas el. paštas amsterdam.nl
Shayegan OmidshafieiGooglePatvirtintas el. paštas google.com
julien perolatDeepMindPatvirtintas el. paštas google.com
Paul MullerPhD Student, DeepmindPatvirtintas el. paštas google.com
Michael KaisersDeepMindPatvirtintas el. paštas deepmind.com
Marc LanctotResearch Scientist, DeepMindPatvirtintas el. paštas google.com
Sjriek AlersFontys university of applied sciencesPatvirtintas el. paštas fontys.nl
Rémi MunosDeepMindPatvirtintas el. paštas inria.fr
Mark RowlandResearch Scientist, DeepMindPatvirtintas el. paštas google.com
Wim MeeussenWillow Garage IncPatvirtintas el. paštas willowgarage.com
Siqi LiuDeepMind, University College of LondonPatvirtintas el. paštas google.com
Thore GraepelGlobal Lead Computational Science, AI & ML at Altos Labs and Chair of Machine Learning, UCLPatvirtintas el. paštas ucl.ac.uk
Luís F. SimõesML AnalyticsPatvirtintas el. paštas esa.int
Marcus MärtensEuropean Space AgencyPatvirtintas el. paštas esa.int
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyPatvirtintas el. paštas tu-berlin.de
Guido de CroonFull professor, Delft University of TechnologyPatvirtintas el. paštas tudelft.nl
Gerhard WeissProfessor of Computer Science and Artificial Intelligence, Maastricht UniversityPatvirtintas el. paštas maastrichtuniversity.nl
Matthias RAUTERBERGEindhoven University of Technology (TU/e)Patvirtintas el. paštas tue.nl

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Daniel Hennes

Research Scientist, Google DeepMind

Patvirtintas el. paštas google.com


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Evolutionary dynamics of multi-agent learning: A survey D Bloembergen, K Tuyls, D Hennes, M Kaisers Journal of Artificial Intelligence Research 53, 659-697, 2015	286	2015
OpenSpiel: A framework for reinforcement learning in games M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ... arXiv preprint arXiv:1908.09453, 2019	175	2019
Multi-robot collision avoidance with localization uncertainty D Hennes, D Claes, W Meeussen, K Tuyls Proceedings of the 11th International Conference on Autonomous Agents and …, 2012	149	2012
Collision avoidance under bounded localization uncertainty D Claes, D Hennes, K Tuyls, W Meeussen 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2012	89	2012
Evolving solutions to TSP variants for active space debris removal D Izzo, I Getzner, D Hennes, LF Simões Proceedings of the 2015 Annual Conference on Genetic and Evolutionary …, 2015	72	2015
A generalized training approach for multiagent learning P Muller, S Omidshafiei, M Rowland, K Tuyls, J Perolat, S Liu, D Hennes, ... arXiv preprint arXiv:1909.12823, 2019	70	2019
Hierarchies of octrees for efficient 3d mapping KM Wurm, D Hennes, D Holz, RB Rusu, C Stachniss, K Konolige, ... 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2011	58	2011
Designing complex interplanetary trajectories for the global trajectory optimization competitions D Izzo, D Hennes, LF Simões, M Märtens Space Engineering: Modeling and Optimization with Case Studies, 151-176, 2016	55	2016
Effective approximations for multi-robot coordination in spatially distributed tasks D Claes, P Robbel, F Oliehoek, K Tuyls, D Hennes, W Van der Hoek Proceedings of the 14th international conference on autonomous agents and …, 2015	49	2015
OctoSLAM: A 3D mapping approach to situational awareness of unmanned aerial vehicles J Fossel, D Hennes, D Claes, S Alers, K Tuyls 2013 International Conference on Unmanned Aircraft Systems (ICUAS), 179-188, 2013	49	2013
Game Plan: What AI can do for Football, and What Football can do for AI K Tuyls, S Omidshafiei, P Muller, Z Wang, J Connor, D Hennes, I Graham, ... Journal of Artificial Intelligence Research 71, 41-88, 2021	47	2021
Learning the optimal state-feedback using deep networks C Sánchez-Sánchez, D Izzo, D Hennes Symposium Series on Computational Intelligence, 2016	47	2016
Novelty search for soft robotic space exploration G Methenitis, D Hennes, D Izzo, A Visser Proceedings of the 2015 annual conference on Genetic and Evolutionary …, 2015	45	2015
Neural replicator dynamics: Multiagent learning via hedging policy gradients D Hennes, D Morrill, S Omidshafiei, R Munos, J Perolat, M Lanctot, ... Proceedings of the 19th International Conference on Autonomous Agents and …, 2020	43*	2020
From motor control to team play in simulated humanoid football S Liu, G Lever, Z Wang, J Merel, SM Eslami, D Hennes, WM Czarnecki, ... arXiv preprint arXiv:2105.12196, 2021	41	2021
Fast approximators for optimal low-thrust hops between main belt asteroids D Hennes, D Izzo, D Landau Symposium Series on Computational Intelligence, 2016	40	2016
Interplanetary Trajectory Planning with Monte Carlo Tree Search D Hennes, D Izzo International Joint Conference on Artificial Intelligence, 2015	38	2015
Mastering the game of Stratego with model-free multiagent reinforcement learning J Perolat, B De Vylder, D Hennes, E Tarassov, F Strub, V de Boer, ... Science 378 (6623), 990-996, 2022	31	2022
Gaussian process estimation of odometry errors for localization and mapping J Hidalgo-Carrió, D Hennes, J Schwendner, F Kirchner 2017 IEEE International Conference on Robotics and Automation (ICRA), 5696-5701, 2017	31	2017
State-coupled replicator dynamics. D Hennes, K Tuyls, M Rauterberg AAMAS (2), 789-796, 2009	31	2009

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