  Mortal bandits have proven to be extremely useful for providing news article
recommendations, running automated online advertising campaigns, and for other
applications where the set of available options changes over time. Previous
work on this problem showed how to regulate exploration of new arms when they
have recently appeared, but they do not adapt when the arms are about to
disappear. Since in most applications we can determine either exactly or
approximately when arms will disappear, we can leverage this information to
improve performance: we should not be exploring arms that are about to
disappear. We provide adaptations of algorithms, regret bounds, and experiments
for this study, showing a clear benefit from regulating greed
(exploration/exploitation) for arms that will soon disappear. We illustrate
numerical performance on the Yahoo! Front Page Today Module User Click Log
Dataset.
