Invention Grant
- Patent Title: Reinforcement learning neural networks grounded in learned visual entities
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Application No.: US16586262Application Date: 2019-09-27
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Publication No.: US10748039B2Publication Date: 2020-08-18
- Inventor: Catalin-Dumitru Ionescu , Tejas Dattatraya Kulkarni
- 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.
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06F16/56 ; G06N3/04 ; G06N3/08

Abstract:
A reinforcement learning neural network system in which internal representations and policies are grounded in visual entities derived from image pixels comprises a visual entity identifying neural network subsystem configured to process image data to determine a set of spatial maps representing respective discrete visual entities. A reinforcement learning neural network subsystem processes data from the set of spatial maps and environmental reward data to provide action data for selecting actions to perform a task.
Public/Granted literature
- US20200104645A1 REINFORCEMENT LEARNING NEURAL NETWORKS GROUNDED IN LEARNED VISUAL ENTITIES Public/Granted day:2020-04-02
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