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You have a partially observable environment with evolving dynamics (non-stationary transition and reward distributions). Logged data comes from multiple behavior policies. How would you estimate the expected return of a new policy and safely improve it, without deploying it, while accounting for uncertainty in both the dynamics and the behavior policies?
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Senior Machine Learning Scientist

Interviewed at Grafton Sciences

5
Oct 17, 2025

You have a partially observable environment with evolving dynamics (non-stationary transition and reward distributions). Logged data comes from multiple behavior policies. How would you estimate the expected return of a new policy and safely improve it, without deploying it, while accounting for uncertainty in both the dynamics and the behavior policies?

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