Multi-armed Bandit Mechanism with Private Histories
نویسندگان
چکیده
The fundamental challenge in bandit problem is the trade off between exploration and exploitation. To minimize the regret in a long period, an algorithm has to explore by actually choosing seemingly suboptimal arms so as to gather more information about them. The exploration obviously has higher short-term regrets. In recommendation of new items, the lifecycles of these items are remarkably short. We try to gather information as plenty as possible in an exploration process and expect we can get rewards in the following exploitation, but the gains are tiny and some newer items come in and next exploration should be start. We must increase the intensity of exploration so as to gather information quickly, but this will draw more regrets.
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