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tempestpy: Easy-to-Use Shielded Reinforcement Learning
Safe exploration is a key challenge in Reinforcement Learning (RL) that aims to prevent agents from making decisions that could cause harm while exploring their environment. Shielding is one such technique that assumes domain knowledge in the form of a model of the environment to decide upon the saf
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