Optimal Feedback in Contests
研究了设计者通过粗粒度二元信号（泊松成功）监控努力时，如何设计动态竞赛以在固定奖品下最大化努力并尽可能缩短时间，发现最优竞赛具有历史依赖终止规则、完全反馈自身成功的政策以及时间不变的预期奖品分配规则。
Abstract We obtain optimal dynamic contests for environments where the designer monitors effort through coarse, binary signals—Poisson successes—and aims to elicit maximum effort, ideally in the least amount of time possible, given a fixed prize. The designer has a vast set of contests to choose from, featuring termination and prize-allocation rules together with real-time feedback for the contestants. Every effort-maximizing contest (which also maximizes total expected successes) has a history-dependent termination rule, a feedback policy that keeps agents fully apprised of their own success, and a prize-allocation rule that grants them, in expectation, a time-invariant share of the prize if they succeed. Any contest that achieves this effort in the shortest possible time must in addition be what we call second chance: once a pre-specified number of successes arrive, the contest enters a countdown phase where contestants are given one last chance to succeed.