Patent ID: 11897133
Assignee: GOOGLE LLC
Field: Handling (Mechanical engineering)
Classification: CPC B  G | IPC B  G

Claim 12:
13. A method implemented by one or more processors, comprising:
during performance of a plurality of episodes by each of a plurality of agents, each of the episodes including performing a task based on a policy neural network representing a reinforcement learning policy for the task:
storing, in a buffer, instances of experience data generated during the episodes by the plurality of agents, each of the instances of the experience data being generated during a corresponding one of the episodes, and being generated at least in part on corresponding output generated using the policy neural network with corresponding policy parameters for the policy neural network for the corresponding episode;

iteratively generating updated policy parameters of the policy neural network, wherein each of the iterations of the iteratively generating comprises generating the updated policy parameters using a group of one or more of the instances of the experience data in the buffer during the iteration; and
by each of the agents in conjunction with a start of each of a plurality of the episodes performed by the agents, updating the policy neural network to be used by the agents in the episode, wherein updating the policy neural network comprises using the updated policy parameters of a most recent iteration of the iteratively generating the updated policy parameters.