Invention Grant
- Patent Title: Reinforcement learning using distributed prioritized replay
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Application No.: US16641751Application Date: 2018-10-29
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Publication No.: US11625604B2Publication Date: 2023-04-11
- Inventor: David Budden , Gabriel Barth-Maron , John Quan , Daniel George Horgan
- Applicant: DeepMind Technologies Limited
- Applicant Address: GB London
- Assignee: DeepMind Technologies Limited
- Current Assignee: DeepMind Technologies Limited
- Current Assignee Address: GB London
- Agency: Fish & Richardson P.C.
- International Application: PCT/EP2018/079566 WO 20181029
- International Announcement: WO2019/081783 WO 20190502
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04 ; G06N20/00 ; G06N3/088

Abstract:
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.
Public/Granted literature
- US20200265305A1 REINFORCEMENT LEARNING USING DISTRIBUTED PRIORITIZED REPLAY Public/Granted day:2020-08-20
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