公开(公告)号：US12271823B2

公开(公告)日：2025-04-08

申请号：US18180754

申请日：2023-03-08

Applicant: DeepMind Technologies Limited

Inventor： Misha Man Ray Denil ,  Tom Schaul ,  Marcin Andrychowicz ,  Joao Ferdinando Gomes de Freitas ,  Sergio Gomez Colmenarejo ,  Matthew William Hoffman ,  David Benjamin Pfau

IPC: G06N3/084 ,  G06N3/044 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for training machine learning models. One method includes obtaining a machine learning model, wherein the machine learning model comprises one or more model parameters, and the machine learning model is trained using gradient descent techniques to optimize an objective function; determining an update rule for the model parameters using a recurrent neural network (RNN); and applying a determined update rule for a final time step in a sequence of multiple time steps to the model parameters.

公开(公告)号：US11663475B2

公开(公告)日：2023-05-30

申请号：US17945622

申请日：2022-09-15

Applicant: DeepMind Technologies Limited

Inventor： David Budden ,  Matthew William Hoffman ,  Gabriel Barth-Maron

IPC: G06N3/08 ,  G06N3/045 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network that is used to select actions to be performed by a reinforcement learning agent interacting with an environment. In particular, the actions are selected from a continuous action space and the system trains the action selection neural network jointly with a distribution Q network that is used to update the parameters of the action selection neural network.

公开(公告)号：US20200293883A1

公开(公告)日：2020-09-17

申请号：US16759519

申请日：2018-10-29

Applicant: DeepMind Technologies Limited

Inventor： David Budden ,  Matthew William Hoffman ,  Gabriel Barth-Maron

IPC: G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network that is used to select actions to be performed by a reinforcement learning agent interacting with an environment. In particular, the actions are selected from a continuous action space and the system trains the action selection neural network jointly with a distribution Q network that is used to update the parameters of the action selection neural network.

公开(公告)号：US11615310B2

公开(公告)日：2023-03-28

申请号：US16302592

申请日：2017-05-19

Applicant: DEEPMIND TECHNOLOGIES LIMITED

Inventor： Misha Man Ray Denil ,  Tom Schaul ,  Marcin Andrychowicz ,  Joao Ferdinando Gomes de Freitas ,  Sergio Gomez Colmenarejo ,  Matthew William Hoffman ,  David Benjamin Pfau

IPC: G06N3/08 ,  G06N3/04 ,  G06N3/084

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for training machine learning models. One method includes obtaining a machine learning model, wherein the machine learning model comprises one or more model parameters, and the machine learning model is trained using gradient descent techniques to optimize an objective function; determining an update rule for the model parameters using a recurrent neural network (RNN); and applying a determined update rule for a final time step in a sequence of multiple time steps to the model parameters.

公开(公告)号：US11481629B2

公开(公告)日：2022-10-25

申请号：US16759519

申请日：2018-10-29

Applicant: DeepMind Technologies Limited

Inventor： David Budden ,  Matthew William Hoffman ,  Gabriel Barth-Maron

IPC: G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network that is used to select actions to be performed by a reinforcement learning agent interacting with an environment. In particular, the actions are selected from a continuous action space and the system trains the action selection neural network jointly with a distribution Q network that is used to update the parameters of the action selection neural network.

公开(公告)号：US11948085B2

公开(公告)日：2024-04-02

申请号：US18303117

申请日：2023-04-19

Applicant: DeepMind Technologies Limited

Inventor： David Budden ,  Matthew William Hoffman ,  Gabriel Barth-Maron

IPC: G06N3/08 ,  G06N3/045

CPC classification number: G06N3/08 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network that is used to select actions to be performed by a reinforcement learning agent interacting with an environment. In particular, the actions are selected from a continuous action space and the system trains the action selection neural network jointly with a distribution Q network that is used to update the parameters of the action selection neural network.

公开(公告)号：US20230409907A1

公开(公告)日：2023-12-21

申请号：US18303117

申请日：2023-04-19

Applicant: Deepmind Technologies Limited

Inventor： David Budden ,  Matthew William Hoffman ,  Gabriel Barth-Maron

IPC: G06N3/08 ,  G06N3/045

CPC classification number: G06N3/08 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network that is used to select actions to be performed by a reinforcement learning agent interacting with an environment. In particular, the actions are selected from a continuous action space and the system trains the action selection neural network jointly with a distribution Q network that is used to update the parameters of the action selection neural network.

公开(公告)号：US20230376771A1

公开(公告)日：2023-11-23

申请号：US18180754

申请日：2023-03-08

Applicant: DeepMind Technologies Limited

Inventor： Misha Man Ray Denil ,  Tom Schaul ,  Marcin Andrychowicz ,  Joao Ferdinando Gomes de Freitas ,  Sergio Gomez Colmenarejo ,  Matthew William Hoffman ,  David Benjamin Pfau

IPC: G06N3/084 ,  G06N3/044 ,  G06N3/045

CPC classification number: G06N3/084 ,  G06N3/044 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for training machine learning models. One method includes obtaining a machine learning model, wherein the machine learning model comprises one or more model parameters, and the machine learning model is trained using gradient descent techniques to optimize an objective function; determining an update rule for the model parameters using a recurrent neural network (RNN); and applying a determined update rule for a final time step in a sequence of multiple time steps to the model parameters.

公开(公告)号：US20230020071A1

公开(公告)日：2023-01-19

申请号：US17945622

申请日：2022-09-15

Applicant: DeepMind Technologies Limited

Inventor： David Budden ,  Matthew William Hoffman ,  Gabriel Barth-Maron

IPC: G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network that is used to select actions to be performed by a reinforcement learning agent interacting with an environment. In particular, the actions are selected from a continuous action space and the system trains the action selection neural network jointly with a distribution Q network that is used to update the parameters of the action selection neural network.