Czarnecki, Wojciech M.

Grandmaster level in StarCraft II using multi-agent reinforcement learning

Vinyals, O., Babuschkin, I., Czarnecki, W. M., Mathieu, M., Dudzik, A., Chung, J., Choi, D. H., Powell, R., Ewalds, T., Georgiev, P., et al. (2019) · Nature

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 3,455

Human-level performance in 3D multiplayer games with population-based reinforcement learning

Jaderberg, M., Czarnecki, W. M., Dunning, I., Marris, L., Lever, G., Castañeda, A. G., Beattie, C., Rabinowitz, N. C., Morcos, A. S., Ruderman, A., et al. (2019) · Science

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 662

Population Based Training of Neural Networks

Jaderberg, M., Dalibard, V., Osindero, S., Czarnecki, W. M., Donahue, J., Razavi, A., Vinyals, O., Green, T., Dunning, I., Simonyan, K., et al. (2017) · arXiv

Machine Learning and Data ClassificationStochastic Gradient Optimization Techniques

Cited by 284

From motor control to team play in simulated humanoid football

Liu, S., Lever, G., Wang, Z., Merel, J., Eslami, S. M. A., Hennes, D., Czarnecki, W. M., Tassa, Y., Omidshafiei, S., Abdolmaleki, A., et al. (2022) · Science Robotics

Reinforcement Learning in RoboticsHuman Motion and Animation

Cited by 88

Open-ended Learning in Symmetric Zero-sum Games

Balduzzi, D., Garnelo, M., Bachrach, Y., Czarnecki, W. M., Perolat, J., Jaderberg, M., & Graepel, T. (2019) · arXiv

Artificial Intelligence in GamesEvolutionary Algorithms and Applications

Cited by 88

Kickstarting Deep Reinforcement Learning

Schmitt, S., Hudson, J. J., Zidek, A., Osindero, S., Doersch, C., Czarnecki, W. M., Leibo, J. Z., Kuttler, H., Zisserman, A., Simonyan, K., et al. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 67

Open-Ended Learning Leads to Generally Capable Agents

Open Ended Learning Team, Stooke, A., Mahajan, A., Barros, C., Deck, C., Bauer, J., Sygnowski, J., Trebacz, M., Jaderberg, M., Mathieu, M., et al. (2021) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 56

A study on the plasticity of neural networks

Berariu, T., Czarnecki, W., De, S., Bornschein, J., Smith, S., Pascanu, R., & Clopath, C. (2021) · arXiv

Domain Adaptation and Few-Shot LearningNeural Networks and Applications

Cited by 3

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity

Garnelo, M., Czarnecki, W. M., Liu, S., Tirumala, D., Oh, J., Gidel, G., van Hasselt, H., & Balduzzi, D. (2021) · arXiv

Artificial Intelligence in GamesEvolutionary Algorithms and Applications

Cited by 3