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Found 2 papers, 1 papers with code
A Flexible Framework for Incorporating Patient Preferences Into Q-Learning
In real-world healthcare problems, there are often multiple competing outcomes of interest, such as treatment efficacy and side effect severity.
Revisiting Bellman Errors for Offline Model Selection
Offline model selection (OMS), that is, choosing the best policy from a set of many policies given only logged data, is crucial for applying offline RL in real-world settings.
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