Dalibard, Valentin

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

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

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

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

RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation

Bousmalis, K., Vezzani, G., Rao, D., Devin, C., Lee, A. X., Bauza, M., Davchev, T., Zhou, Y., Gupta, A., Raju, A., et al. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 13