具有执行不确定性的网络任务分配
Task Allocation on Networks with Execution Uncertainty
摘要：
我们研究一个单一的任务分配问题，每个工人连接到其他一些工人，形成一个网络，任务请求者只连接到一些工人。我们的目标是设计一个分配机制，这样每个工人都有动力邀请她的邻居加入分配，尽管他们正在竞争这项任务。此外，每个工人的表现是不确定的，这是建模为她的任务执行的质量水平。文献提出了解决不确定性问题的解决方案，即在验证其执行后支付。在这里，我们将问题扩展到网络设置。挑战在于，请求者依赖于工作者相互邀请来找到最佳工作者，并且每个工作者的性能对于任务请求者来说也是未知的。在本文中，我们提出了一种新的机制，以解决这两个挑战在同一时间。该机制保证邀请更多的工人并根据她的真实能力报告/执行是每个工人的主导策略。我们相信，新的解决方案可以广泛应用于由众包和竞赛等社会联系驱动的数字经济。
英文摘要：
We study a single task allocation problem where each worker connects to some other workers to form a network and the task requester only connects to some of the workers. The goal is to design an allocation mechanism such that each worker is incentivized to invite her neighbours to join the allocation, although they are competing for the task. Moreover, the performance of each worker is uncertain, which is modelled as the quality level of her task execution. The literature has proposed solutions to tackle the uncertainty problem by paying them after verifying their execution. Here, we extend the problem to the network setting. The challenge is that the requester relies on the workers to invite each other to find the best worker, and the performance of each worker is also unknown to the task requester. In this paper, we propose a new mechanism to solve the two challenges at the same time. The mechanism guarantees that inviting more workers and reporting/performing according to her true ability is a dominant strategy for each worker. We believe that the new solution can be widely applied in the digital economy powered by social connections such as crowdsourcing and contests.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
