Why Non-myopic Bayesian Optimization is Promising and How Far Should We Look-ahead? A Study via Rollout

4 Nov 2019Xubo YueRaed Al Kontar

Lookahead, also known as non-myopic, Bayesian optimization (BO) aims to find optimal sampling policies through solving a dynamic programming (DP) formulation that maximizes a long-term reward over a rolling horizon. Though promising, lookahead BO faces the risk of error propagation through its increased dependence on a possibly mis-specified model... (read more)

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