OPENTECHNICAL PUBLICATION
OT-2026-000000879

Intermediate policy training system and method for agent

Published: 2026-09-15T19:03:32.006436Z
Permanent URL: https://opentechnical.org/p/OT-2026-000000879
Categories: Robotics & Automation > Robot Architectures

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ABSTRACT

An intermediate policy training method for agent is provided. This method
includes: selecting a source and a target policy from a plurality of policies.
Each policy is configured to drive an agent to perform a plurality of actions
to be in a plurality of states. Each state includes a plurality of physical
properties. The method further includes: respectively selecting one from the
source policy and the target policy as a source state and a target state;
training an intermediate policy by a reinforcement learning to transition the
agent from the source state to the target state over an episode, where the
reinforcement learning includes an annealing function for setting a plurality
of tolerance boundaries of the plurality of physical properties, and the
tolerance boundaries gradually shrink during the episode.

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OpenTechnical publication OT-2026-000000879
Published 2026-09-15T19:03:32.006436Z
https://opentechnical.org/p/OT-2026-000000879