Deepmind Technologies Limited

Gdm Holding LLC

Francesco Nori

Konstantinos Bousmalis

Thomas Lampe

Yusuf Aytar

Alexandre Galashov

Rae Chan Jeong

Yuxiang Zhou

Jacqueline Ok-chan Kay

Jost Tobias Springenberg

David Khosid

Jacqueline Ok-Chan Kay

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a policy neural network for use in controlling a real-world agent in a real-world environment. One of the methods includes training the policy neural network by optimizing a first task-specific objective that measures a performance of the policy neural network in controlling a simulated version of the real-world agent; and then training the policy neural network by jointly optimizing (i) a self-supervised objective that measures at least a performance of internal representations generated by the policy neural network on a self-supervised task performed on real-world data and (ii) a second task-specific objective that measures the performance of the policy neural network in controlling the simulated version of the real-world agent.

Domain adaptation for robotic control using self-supervised learning

Growing community of inventors

London, United Kingdom

Francesco Nori