CONTROLLING AGENTS USING RELATIVE VARIATIONAL INTRINSIC CONTROL

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a policy neural network for use in controlling an agent using relative variational intrinsic control. In one aspect, a method includes: selecting a skill from a set of skills; generating a trajectory by controlling the agent using the policy neural network while the policy neural network is conditioned on the selected skill; processing an initial observation and a last observation using a relative discriminator neural network to generate a relative score; processing the last observation using an absolute discriminator neural network to generate an absolute score; generating a reward for the trajectory from the absolute score corresponding to the selected skill and the relative score corresponding to the selected skill; and training the policy neural network on the reward for the trajectory.