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Poster
On Explore-Then-Commit strategies
Aurélien Garivier · Tor Lattimore · Emilie Kaufmann

Mon Dec 05 09:00 AM -- 12:30 PM (PST) @ Area 5+6+7+8 #118
in Monday Posters »

We study the problem of minimising regret in two-armed bandit problems with Gaussian rewards. Our objective is to use this simple setting to illustrate that strategies based on an exploration phase (up to a stopping time) followed by exploitation are necessarily suboptimal. The results hold regardless of whether or not the difference in means between the two arms is known. Besides the main message, we also refine existing deviation inequalities, which allow us to design fully sequential strategies with finite-time regret guarantees that are (a) asymptotically optimal as the horizon grows and (b) order-optimal in the minimax sense. Furthermore we provide empirical evidence that the theory also holds in practice and discuss extensions to non-gaussian and multiple-armed case.

Keywords: Bandit Algorithms

Author Information

Aurélien Garivier (Ecole Normale Supérieure de Lyon)
Tor Lattimore (DeepMind)
Emilie Kaufmann (Telecom ParisTech)

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