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公开(公告)号:US20210117801A1
公开(公告)日:2021-04-22
申请号:US17093373
申请日:2020-11-09
Applicant: DeepMind Technologies Limited
Inventor: Alexander Benjamin Graves , Ivo Danihelka , Timothy James Alexander Harley , Malcolm Kevin Campbell Reynolds , Gregory Duncan Wayne
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting neural networks with an external memory. One of the systems includes a memory interface subsystem that is configured to perform operations comprising determining a respective content-based weight for each of a plurality of locations in an external memory; determining a respective allocation weight for each of the plurality of locations in the external memory; determining a respective final writing weight for each of the plurality of locations in the external memory from the respective content-based weight for the location and the respective allocation weight for the location; and writing data defined by the write vector to the external memory in accordance with the final writing weights.
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公开(公告)号:US20180260708A1
公开(公告)日:2018-09-13
申请号:US15977923
申请日:2018-05-11
Applicant: DeepMind Technologies Limited
Inventor: Volodymyr Mnih , Adrià Puigdomènech Badia , Alexander Benjamin Graves , Timothy James Alexander Harley , David Silver , Koray Kavukcuoglu
CPC classification number: G06N3/08 , G06N3/04 , G06N3/0454
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for asynchronous deep reinforcement learning. One of the systems includes a plurality of workers, wherein each worker is configured to operate independently of each other worker, and wherein each worker is associated with a respective actor that interacts with a respective replica of the environment during the training of the deep neural network.
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公开(公告)号:US12020155B2
公开(公告)日:2024-06-25
申请号:US17733594
申请日:2022-04-29
Applicant: DeepMind Technologies Limited
Inventor: Volodymyr Mnih , Adrià Puigdomènech Badia , Alexander Benjamin Graves , Timothy James Alexander Harley , David Silver , Koray Kavukcuoglu
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for asynchronous deep reinforcement learning. One of the systems includes a plurality of workers, wherein each worker is configured to operate independently of each other worker, and wherein each worker is associated with a respective actor that interacts with a respective replica of the environment during the training of the deep neural network.
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公开(公告)号:US11593646B2
公开(公告)日:2023-02-28
申请号:US16767049
申请日:2019-02-05
Applicant: DeepMind Technologies Limited
Inventor: Hubert Josef Soyer , Lasse Espeholt , Karen Simonyan , Yotam Doron , Vlad Firoiu , Volodymyr Mnih , Koray Kavukcuoglu , Remi Munos , Thomas Ward , Timothy James Alexander Harley , Iain Robert Dunning
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network used to select actions to be performed by an agent interacting with an environment. In one aspect, a system comprises a plurality of actor computing units and a plurality of learner computing units. The actor computing units generate experience tuple trajectories that are used by the learner computing units to update learner action selection neural network parameters using a reinforcement learning technique. The reinforcement learning technique may be an off-policy actor critic reinforcement learning technique.
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公开(公告)号:US11151443B2
公开(公告)日:2021-10-19
申请号:US15424685
申请日:2017-02-03
Applicant: DeepMind Technologies Limited
Inventor: Ivo Danihelka , Gregory Duncan Wayne , Fu-min Wang , Edward Thomas Grefenstette , Jack William Rae , Alexander Benjamin Graves , Timothy Paul Lillicrap , Timothy James Alexander Harley , Jonathan James Hunt
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting neural networks with an external memory. One of the systems includes a sparse memory access subsystem that is configured to perform operations comprising generating a sparse set of reading weights that includes a respective reading weight for each of the plurality of locations in the external memory using the read key, reading data from the plurality of locations in the external memory in accordance with the sparse set of reading weights, generating a set of writing weights that includes a respective writing weight for each of the plurality of locations in the external memory, and writing the write vector to the plurality of locations in the external memory in accordance with the writing weights.
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公开(公告)号:US10346741B2
公开(公告)日:2019-07-09
申请号:US15977923
申请日:2018-05-11
Applicant: DeepMind Technologies Limited
Inventor: Volodymyr Mnih , Adrià Puigdomènech Badia , Alexander Benjamin Graves , Timothy James Alexander Harley , David Silver , Koray Kavukcuoglu
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for asynchronous deep reinforcement learning. One of the systems includes a plurality of workers, wherein each worker is configured to operate independently of each other worker, and wherein each worker is associated with a respective actor that interacts with a respective replica of the environment during the training of the deep neural network.
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公开(公告)号:US12299575B2
公开(公告)日:2025-05-13
申请号:US17093373
申请日:2020-11-09
Applicant: DeepMind Technologies Limited
Inventor: Alexander Benjamin Graves , Ivo Danihelka , Timothy James Alexander Harley , Malcolm Kevin Campbell Reynolds , Gregory Duncan Wayne
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting neural networks with an external memory. One of the systems includes a memory interface subsystem that is configured to perform operations comprising determining a respective content-based weight for each of a plurality of locations in an external memory; determining a respective allocation weight for each of the plurality of locations in the external memory; determining a respective final writing weight for each of the plurality of locations in the external memory from the respective content-based weight for the location and the respective allocation weight for the location; and writing data defined by the write vector to the external memory in accordance with the final writing weights.
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公开(公告)号:US11907821B2
公开(公告)日:2024-02-20
申请号:US16586236
申请日:2019-09-27
Applicant: DeepMind Technologies Limited
Inventor: Ang Li , Valentin Clement Dalibard , David Budden , Ola Spyra , Maxwell Elliot Jaderberg , Timothy James Alexander Harley , Sagi Perel , Chenjie Gu , Pramod Gupta
IPC: G06N20/20 , G06F16/901 , G06N5/04
CPC classification number: G06N20/20 , G06F16/9024 , G06N5/04
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a machine learning model. A method includes: maintaining a plurality of training sessions; assigning, to each worker of one or more workers, a respective training session of the plurality of training sessions; repeatedly performing operations until meeting one or more termination criteria, the operations comprising: receiving an updated training session from a respective worker of the one or more workers, selecting a second training session, selecting, based on comparing the updated training session and the second training session using a fitness evaluation function, either the updated training session or the second training session as a parent training session, generating a child training session from the selected parent training session, and assigning the child training session to an available worker, and selecting a candidate model to be a trained model for the machine learning model.
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公开(公告)号:US11783182B2
公开(公告)日:2023-10-10
申请号:US17170316
申请日:2021-02-08
Applicant: DeepMind Technologies Limited
Inventor: Volodymyr Mnih , Adrià Puigdomènech Badia , Alexander Benjamin Graves , Timothy James Alexander Harley , David Silver , Koray Kavukcuoglu
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for asynchronous deep reinforcement learning. One of the systems includes a plurality of workers, wherein each worker is configured to operate independently of each other worker, and wherein each worker is associated with a respective actor that interacts with a respective replica of the environment during the training of the deep neural network.
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公开(公告)号:US20220261647A1
公开(公告)日:2022-08-18
申请号:US17733594
申请日:2022-04-29
Applicant: DeepMind Technologies Limited
Inventor: Volodymyr Mnih , Adrià Puigdomènech Badia , Alexander Benjamin Graves , Timothy James Alexander Harley , David Silver , Koray Kavukcuoglu
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for asynchronous deep reinforcement learning. One of the systems includes a plurality of workers, wherein each worker is configured to operate independently of each other worker, and wherein each worker is associated with a respective actor that interacts with a respective replica of the environment during the training of the deep neural network.
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