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Title:

Bullet-Safety-Gym: A Framework for Constrained Reinforcement Learning

Document type:
Report / Forschungsbericht
Author(s):
Sven Gronauer
Abstract:
The Bullet-Safety-Gym is an open-source framework to train and assess safety specifications in constrained reinforcement learning problems. We have implemented 16 environments differing in complexity and design. The framework is entirely written in Python and builds open the freely available PyBullet physics engine. Based on our environments, we evaluate five state-of-the-art policy gradient algorithms and provide results as a baseline for future research. To this end, we discuss our findings a...     »
Keywords:
Reinforcement Learning, Safety, Machine Learning
Contracting organization:
TUM Department of Electrical and Computer Engineering
Year:
2022
Quarter:
1. Quartal
Monat:
Jan
Language:
en
DOI:
doi:10.14459/2022md1639974
CC license:
by, http://creativecommons.org/licenses/by/4.0
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