HPRS: hierarchical potential-based reward shaping from task specifications
The automatic synthesis of policies for robotics systems through reinforcement learning relies upon, and is intimately guided by, a reward signal. Consequently, this signal should faithfully reflect the designer’s intentions, which are often expressed as a collection of high-level requirements. Seve...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-02-01
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Series: | Frontiers in Robotics and AI |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/frobt.2024.1444188/full |
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