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This is a record of a document published elsewhere, first published by the United States Patent and Trademark Office, as US-12576515-B2, on 17 March 2026. OpenTechnical did not first disclose it. The identifier, hashes and timestamps below record what this library served and when, not when the material became public. View the original.

OT-2026-000001838

Off-line learning for robot control using a reward prediction model

Published
Permanent URL
Classification
Robotics & Automation › Robot Architectures
Inventors
Reed Scott Ellison, ZOLNA KONRAD
Assignee
GDM HOLDING LLC
Original source
US-12576515-B2, the United States Patent and Trademark Office, 17 March 2026
Document SHA-256
4190c3f7d4315025013ddeb61b06024fee492b5d058a20fa58b7e7a5c3554c13

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for off-line learning using a reward prediction model. One of the methods includes obtaining robot experience data; training, on a first subset of the robot experience data, a reward prediction model that receives a reward input comprising an input observation and generates as output a reward prediction that is a prediction of a task-specific reward for the particular task that should be assigned to the input observation; processing experiences in the robot experience data using the trained reward prediction model to generate a respective reward prediction for each of the processed experiences; and training a policy neural network on (i) the processed experiences and (ii) the respective reward predictions for the processed experiences.

Publication information

Citation

OpenTechnical Publication OT-2026-000001838, “Off-line learning for robot control using a reward prediction model,” published September 15, 2026 at 19:08:58 UTC, https://opentechnical.org/p/OT-2026-000001838.

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