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公开(公告)号：US20240054328A1
公开(公告)日：2024-02-15
申请号：US18144810
申请日：2023-05-08
Applicant: DeepMind Technologies Limited
Inventor： Yujia Li , Christopher James Dyer , Oriol Vinyals
IPC: G06N3/047 , G06F16/901 , G06F17/18 , G06N3/08 , G06N3/045
CPC classification number: G06N3/047 , G06F16/9024 , G06F17/18 , G06N3/08 , G06N3/045
Abstract: There is described a neural network system for generating a graph, the graph comprising a set of nodes and edges. The system comprises one or more neural networks configured to represent a probability distribution over sequences of node generating decisions and/or edge generating decisions, and one or more computers configured to sample the probability distribution represented by the one or more neural networks to generate a graph.
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公开(公告)号：US11328183B2
公开(公告)日：2022-05-10
申请号：US17019919
申请日：2020-09-14
Applicant: DeepMind Technologies Limited
Inventor： Daniel Pieter Wierstra , Yujia Li , Razvan Pascanu , Peter William Battaglia , Theophane Guillaume Weber , Lars Buesing , David Paul Reichert , Arthur Clement Guez , Danilo Jimenez Rezende , Adrià Puigdomènech Badia , Oriol Vinyals , Nicolas Manfred Otto Heess , Sebastien Henri Andre Racaniere
Abstract: A neural network system is proposed. The neural network can be trained by model-based reinforcement learning to select actions to be performed by an agent interacting with an environment, to perform a task in an attempt to achieve a specified result. The system may comprise at least one imagination core which receives a current observation characterizing a current state of the environment, and optionally historical observations, and which includes a model of the environment. The imagination core may be configured to output trajectory data in response to the current observation, and/or historical observations. The trajectory data comprising a sequence of future features of the environment imagined by the imagination core. The system may also include a rollout encoder to encode the features, and an output stage to receive data derived from the rollout embedding and to output action policy data for identifying an action based on the current observation.
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公开(公告)号：US20200279151A1
公开(公告)日：2020-09-03
申请号：US16759525
申请日：2018-10-29
Applicant: DEEPMIND TECHNOLOGIES LIMITED
Inventor： Yujia Li , Christopher James Dyer , Oriol Vinyals
IPC: G06N3/04 , G06N3/08 , G06F16/901 , G06F17/18
Abstract: There is described a neural network system for generating a graph, the graph comprising a set of nodes and edges. The system comprises one or more neural networks configured to represent a probability distribution over sequences of node generating decisions and/or edge generating decisions, and one or more computers configured to sample the probability distribution represented by the one or more neural networks to generate a graph.
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公开(公告)号：US20200234145A1
公开(公告)日：2020-07-23
申请号：US16749252
申请日：2020-01-22
Applicant: DeepMind Technologies Limited
Inventor： Hanjun Dai , Yujia Li , Chenglong Wang , Rishabh Singh , Po-Sen Huang , Pushmeet Kohli
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting actions to be performed by an agent interacting with an environment. In one aspect, a method comprises: obtaining a graph of nodes and edges that represents an interaction history of the agent with the environment; generating an encoded representation of the graph representing the interaction history of the agent with the environment; processing an input based on the encoded representation of the graph using an action selection neural network, in accordance with current values of action selection neural network parameters, to generate an action selection output; and selecting an action from a plurality of possible actions to be performed by the agent using the action selection output generated by the action selection neural network.
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公开(公告)号：US12131248B2
公开(公告)日：2024-10-29
申请号：US18144810
申请日：2023-05-08
Applicant: DeepMind Technologies Limited
Inventor： Yujia Li , Christopher James Dyer , Oriol Vinyals
CPC classification number: G06N3/047 , G06F16/9024 , G06F17/18 , G06N3/045 , G06N3/08
Abstract: There is described a neural network system for generating a graph, the graph comprising a set of nodes and edges. The system comprises one or more neural networks configured to represent a probability distribution over sequences of node generating decisions and/or edge generating decisions, and one or more computers configured to sample the probability distribution represented by the one or more neural networks to generate a graph.
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Patent Agency Ranking
公开(公告)号：US20230196146A1
公开(公告)日：2023-06-22
申请号：US18168123
申请日：2023-02-13
Applicant: DeepMind Technologies Limited
Inventor： Yujia Li , Victor Constant Bapst , Vinicius Zambaldi , David Nunes Raposo , Adam Anthony Santoro
Abstract: A neural network system is proposed, including an input network for extracting, from state data, respective entity data for each a plurality of entities which are present, or at least potentially present, in the environment. The entity data describes the entity. The neural network contains a relational network for parsing this data, which includes one or more attention blocks which may be stacked to perform successive actions on the entity data. The attention blocks each include a respective transform network for each of the entities. The transform network for each entity is able to transform data which the transform network receives for the entity into modified entity data for the entity, based on data for a plurality of the other entities. An output network is arranged to receive data output by the relational network, and use the received data to select a respective action.
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公开(公告)号：US20210089834A1
公开(公告)日：2021-03-25
申请号：US17114324
申请日：2020-12-07
Applicant: DeepMind Technologies Limited
Inventor： Daniel Pieter Wierstra , Yujia Li , Razvan Pascanu , Peter William Battaglia , Theophane Guillaume Weber , Lars Buesing , David Paul Reichert , Oriol Vinyals , Nicolas Manfred Otto Heess , Sebastien Henri Andre Racaniere
Abstract: A neural network system is proposed to select actions to be performed by an agent interacting with an environment to perform a task in an attempt to achieve a specified result. The system may include a controller to receive state data and context data, and to output action data. The system may also include an imagination module to receive the state and action data, and to output consequent state data. The system may also include a manager to receive the state data and the context data, and to output route data which defines whether the system is to execute an action or to imagine. The system may also include a memory to store the context data.
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公开(公告)号：US20200293838A1
公开(公告)日：2020-09-17
申请号：US16818932
申请日：2020-03-13
Applicant: DeepMind Technologies Limited
Inventor： Yujia Li , Vinod Nair , Felix Axel Gimeno Gil , Aditya Paliwal , Miles C. Lubin
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a schedule for a computation graph. One of the methods includes obtaining data representing an input computation graph; processing the data representing the input computation graph using a graph neural network to generate one or more instance-specific proposal distributions; and generating a schedule for the input computation graph by performing an optimization algorithm in accordance with the one or more instance-specific proposal distributions.
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公开(公告)号：US11636347B2
公开(公告)日：2023-04-25
申请号：US16749252
申请日：2020-01-22
Applicant: DeepMind Technologies Limited
Inventor： Hanjun Dai , Yujia Li , Chenglong Wang , Rishabh Singh , Po-Sen Huang , Pushmeet Kohli
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting actions to be performed by an agent interacting with an environment. In one aspect, a method comprises: obtaining a graph of nodes and edges that represents an interaction history of the agent with the environment; generating an encoded representation of the graph representing the interaction history of the agent with the environment; processing an input based on the encoded representation of the graph using an action selection neural network, in accordance with current values of action selection neural network parameters, to generate an action selection output; and selecting an action from a plurality of possible actions to be performed by the agent using the action selection output generated by the action selection neural network.
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公开(公告)号：US11580429B2
公开(公告)日：2023-02-14
申请号：US16417580
申请日：2019-05-20
Applicant: DeepMind Technologies Limited
Inventor： Yujia Li , Victor Constant Bapst , Vinicius Zambaldi , David Nunes Raposo , Adam Anthony Santoro
Abstract: A neural network system is proposed, including an input network for extracting, from state data, respective entity data for each a plurality of entities which are present, or at least potentially present, in the environment. The entity data describes the entity. The neural network contains a relational network for parsing this data, which includes one or more attention blocks which may be stacked to perform successive actions on the entity data. The attention blocks each include a respective transform network for each of the entities. The transform network for each entity is able to transform data which the transform network receives for the entity into modified entity data for the entity, based on data for a plurality of the other entities. An output network is arranged to receive data output by the relational network, and use the received data to select a respective action.
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