Preserving Expert-Level Privacy in Offline Reinforcement Learning

The offline reinforcement learning (RL) problem aims to learn an optimal policy from historical data collected by one or more behavioural policies (experts) by interacting with an environment. However, the individual experts may be privacy-sensitive in that the learnt policy may retain information a...

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Hauptverfasser:	Sharma, Navodita, Vinod, Vishnu, Thakurta, Abhradeep, Agarwal, Alekh, Balle, Borja, Dann, Christoph, Raghuveer, Aravindan
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Cryptography and Security Computer Science - Learning
Online-Zugang:	Volltext bestellen
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