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Full Research Paperbacks 2024, May 610, 2024, Auckland, New ZealandSafe Reinforcement Learning with Free form Natural Language
Constraints and PreTrained Language Models
Hangzhou Lounge ZhangZiyan
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Safe reinforcement learning refers to a framework within machine learning that emphasizes training agents in a manner that avoids harmful consequences or risks, ensuring that the learned policies are safe to deploy in real-world environments.
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Reports on safe reinforcement learning must include information on the algorithms used, safety protocols in place, risk analysis results, data sources, and any demonstrations of the effectiveness and safety of the learned policies.
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