Given the task definition and input, reply with output. In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

<lb>Sequentially learning to place items in multi-position displays or lists is a task that can be cast into the<lb>multiple-play semi-bandit setting. However, a major concern in this context is when the system cannot decide<lb>whether the user feedback for each item is actually exploitable. Indeed, much of the content may have been<lb>simply ignored by the user. The present work proposes to exploit available information regarding the display<lb>position bias under the so-called Position-based click model (PBM). We first discuss how this model differs<lb>from the Cascade model and its variants considered in several recent works on multiple-play bandits. We<lb>then provide a novel regret lower bound for this model as well as computationally efficient algorithms that<lb>display good empirical and theoretical performance.
Multiple-Play Bandits in the Position-Based Model