Reinforcement learning using distributed prioritized replay

    公开(公告)号:US11625604B2

    公开(公告)日:2023-04-11

    申请号:US16641751

    申请日:2018-10-29

    摘要: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training an action selection neural network used to select actions to be performed by an agent interacting with an environment. One of the systems includes (i) a plurality of actor computing units, in which each of the actor computing units is configured to maintain a respective replica of the action selection neural network and to perform a plurality of actor operations, and (ii) one or more learner computing units, in which each of the one or more learner computing units is configured to perform a plurality of learner operations.

    REINFORCEMENT LEARNING USING DISTRIBUTED PRIORITIZED REPLAY

    公开(公告)号:US20200265305A1

    公开(公告)日:2020-08-20

    申请号:US16641751

    申请日:2018-10-29

    IPC分类号: G06N3/08 G06N20/00

    摘要: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training an action selection neural network used to select actions to be performed by an agent interacting with an environment. One of the systems includes (i) a plurality of actor computing units, in which each of the actor computing units is configured to maintain a respective replica of the action selection neural network and to perform a plurality of actor operations, and (ii) one or more learner computing units, in which each of the one or more learner computing units is configured to perform a plurality of learner operations.