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arXiv · 1505.00369

Batched bandit problems

Vianney Perchet·Philippe Rigollet·Sylvain Chassang·Erik Snowberg
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Abstract

Motivated by practical applications, chiefly clinical trials, we study the regret achievable for stochastic bandits under the constraint that the employed policy must split trials into a small number of batches. We propose a simple policy, and show that a very small number of batches gives close to minimax optimal regret bounds. As a byproduct, we derive optimal policies with low switching cost for stochastic bandits.

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Vianney Perchet, Philippe Rigollet, Sylvain Chassang, Erik Snowberg. 2016-03-29. Batched bandit problems. https://doi.org/10.1214/15-aos1381

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