Optimal AI recommendation policies under correlated features require an explore-then-commit structure rather than stationary policies, with NP-hard computation and a DP algorithm for finite horizons.
arXiv preprint arXiv:2007.12161 , year=
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Human Decision-Making with AI Assistance under Correlated Features
Optimal AI recommendation policies under correlated features require an explore-then-commit structure rather than stationary policies, with NP-hard computation and a DP algorithm for finite horizons.