Distributional reinforcement learning using quantile function neural networks

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United States of America

PATENT NO 12205032
APP PUB NO 20240135182A1
SERIAL NO

18542476

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Abstract

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Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting an action to be performed by a reinforcement learning agent interacting with an environment. In one aspect, a method comprises: receiving a current observation; for each action of a plurality of actions: randomly sampling one or more probability values; for each probability value: processing the action, the current observation, and the probability value using a quantile function network to generate an estimated quantile value for the probability value with respect to a probability distribution over possible returns that would result from the agent performing the action in response to the current observation; determining a measure of central tendency of the one or more estimated quantile values; and selecting an action to be performed by the agent in response to the current observation using the measures of central tendency for the actions.

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Patent Owner(s)

  • DEEPMIND TECHNOLOGIES LIMITED

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Dabney, William Clinton London, GB 11 85
Ostrovski, Georg London, GB 5 2

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