REINFORCEMENT LEARNING NEURAL NETWORKS GROUNDED IN LEARNED VISUAL ENTITIES

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 resp...

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Bibliographic Details
Main Authors IONESCU, Catalin-Dumitru, KULKARNI, Tejas Dattatraya
Format Patent
LanguageEnglish
French
German
Published 26.06.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary: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.
Bibliography:Application Number: EP20190782529