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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-2026104679-A1, on 16 April 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-2026-000000416

Computer-implemented method for generating at least one weighted training example, use of at least one weighted training example for training a behavior planner, behavior planner

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Sensors, Controls & Machine Vision › Industrial Control
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US-2026104679-A1, the United States Patent and Trademark Office, 16 April 2026
Document SHA-256
4c325134474b2f795a7a2acdf8e5e42a8ea9b9d9817afe7d327a7822aaf4da1e

Abstract

A computer-implemented method for generating at least one weighted training example for training a behavior planner for an at least partially automatically driving vehicle or a robot, wherein each training example is a tuple of a state and a corresponding specified target behavior. The method includes: extracting a state from a pre-provided initial training example as the initial state; rolling out a planning strategy of the behavior planner starting from the initial state within a simulation for generating a simulated behavior; terminating the simulation based on a termination condition; evaluating the initial state and/or a state encountered by the simulated behavior in the simulation; weighting a training example on the based on the evaluation of its state and/or at least one state encountered by the simulated behavior after this, wherein the training example is the initial training example and/or a training example newly generated based on an encountered state.

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OpenTechnical Publication OT-2026-000000416, “Computer-implemented method for generating at least one weighted training example, use of at least one weighted training example for training a behavior planner, behavior planner,” published September 15, 2026 at 19:02:51 UTC, https://opentechnical.org/p/OT-2026-000000416.

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