Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting actions to be performed by an agent that interacts with an environment. In one aspect, a system comprises: an action selection subsystem that selects actions to be performed by the agent using an action selection policy generated using an action selection neural network; a reward subsystem that is configured to: receive an observation characterizing a current state of the environment and an observation characterizing a goal state of the environment; generate a reward using an embedded representation of the observation characterizing the current state of the environment and an embedded representation of the observation characterizing the goal state of the environment; and a training subsystem that is configured to train the action selection neural network based on the rewards generated by the reward subsystem using reinforcement learning techniques.
Unsupervised control using learned rewards