Patent · US Active

Environment prediction using reinforcement learning

US10733501B2 · kind B2 · utility

3Cited by
1References
20Claims
0Family size

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Key dates

Filing dateMay 3, 2019
Grant dateAug 4, 2020
Priority date
Expiry dateMay 3, 2039

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06N3/088
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for prediction of an outcome related to an environment. In one aspect, a system comprises a state representation neural network that is configured to: receive an observation characterizing a state of an environment being interacted with by an agent and process the observation to generate an internal state representation of the environment state; a prediction neural network that is configured to receive a current internal state representation of a current environment state and process the current internal state representation to generate a predicted subsequent state representation of a subsequent state of the environment and a predicted reward for the subsequent state; and a value prediction neural network that is configured to receive a current internal state representation of a current environment state and process the current internal state representation to generate a value prediction.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.