Robustness of Reinforcement Learning Systems in Real-World Environments
Reinforcement Learning (RL) is recognized as a promising paradigm to improve numerous decision-making processes in the real world, potentially constituting the core of many future autonomous systems. However, despite its popularity across multiple fields, the number of proofs of concept in the liter...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/153087 |