Open AccessConservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning
Author(s) -
Yecheng Jason,
Andrew Shen,
Osbert Bastani,
J. Dinesh
Publication year - 2022
Publication title -
proceedings of the aaai conference on artificial intelligence
Language(s) - English
Resource type - Journals
eISSN - 2374-3468
pISSN - 2159-5399
DOI - 10.1609/aaai.v36i5.20478
Subject(s) - reinforcement learning , computer science , constraint (computer aided design) , mathematical optimization , imperfect , code (set theory) , penalty method , artificial intelligence , engineering , mathematics , set (abstract data type) , mechanical engineering , linguistics , philosophy , programming language
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