- 专利标题: Reinforcement learning using distributed prioritized replay
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申请号: US16641751申请日: 2018-10-29
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公开(公告)号: US11625604B2公开(公告)日: 2023-04-11
- 发明人: David Budden , Gabriel Barth-Maron , John Quan , Daniel George Horgan
- 申请人: DeepMind Technologies Limited
- 申请人地址: GB London
- 专利权人: DeepMind Technologies Limited
- 当前专利权人: DeepMind Technologies Limited
- 当前专利权人地址: GB London
- 代理机构: Fish & Richardson P.C.
- 国际申请: PCT/EP2018/079566 WO 20181029
- 国际公布: WO2019/081783 WO 20190502
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G06N3/04 ; G06N20/00 ; G06N3/088
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.
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