Method of generating training data for training a neural network, method of training a neural network and using neural network for autonomous operations

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United States of America Patent

PATENT NO 11688160
APP PUB NO 20190220744A1
SERIAL NO

16248543

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Abstract

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A method of generating training data for training a neural network, method of training a neural network and using a neural network for autonomous operations, related devices and systems. In one aspect, a neural network for autonomous operation of an object in an environment is trained. Policy values are generated based on a sample data set. An approximate action-value function is generated from the policy values. A set of approximated policy values is generated using the approximate action-value function for all states in the sample data set for all possible actions. A training target for the neural network is calculated based on the approximated policy values. A training error is calculated as the difference between the training target and the policy value for the corresponding state-action pair in the sample data set. At least some of the parameters of the neural network are updated to minimize the training error.

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Patent Owner(s)

Patent OwnerAddress
SHENZHEN YINWANG INTELLIGENT TECHNOLOGIES CO LTDSHENZHEN GUANGDONG 518129

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Yao, Hengshuai Markham, CA 5 94

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