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公开(公告)号:US20230325635A1
公开(公告)日:2023-10-12
申请号:US18025304
申请日:2021-09-10
Applicant: DeepMind Technologies Limited
Inventor: David Constantine Patrick Warde-Farley , Steven Stenberg Hansen , Volodymyr Mnih , Kate Alexandra Baumli
Abstract: 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.