Daniel Hennes
Daniel Hennes
Research Scientist, Google DeepMind
Patvirtintas el. paštas
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
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
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
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
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
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
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
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
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
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
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
Learning the optimal state-feedback using deep networks
C Sánchez-Sánchez, D Izzo, D Hennes
Symposium Series on Computational Intelligence, 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
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
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
Fast approximators for optimal low-thrust hops between main belt asteroids
D Hennes, D Izzo, D Landau
Symposium Series on Computational Intelligence, 2016
Interplanetary Trajectory Planning with Monte Carlo Tree Search
D Hennes, D Izzo
International Joint Conference on Artificial Intelligence, 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
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
State-coupled replicator dynamics.
D Hennes, K Tuyls, M Rauterberg
AAMAS (2), 789-796, 2009
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Straipsniai 1–20