论文标题
具有执行不确定性的网络上的任务分配
Task Allocation on Networks with Execution Uncertainty
论文作者
论文摘要
我们研究一个任务分配问题，每个工人都连接到其他一些工人形成网络，而任务请求者仅连接到某些工人。目的是设计一种分配机制，以便激励每个工人邀请邻居加入分配，尽管他们正在争夺任务。此外，每个工人的绩效都是不确定的，该绩效被建模为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，通过验证其处决后付款。在这里，我们将问题扩展到网络设置。挑战在于，请求者依靠工人互相邀请找到最佳工人，并且每个工人的绩效也是任务请求者的不知道。在本文中，我们提出了一种新的机制来同时解决这两个挑战。该机制可以确保邀请更多的工人并根据她的真实能力报告/履行行为是每个工人的主要策略。我们认为，新解决方案可以广泛应用于由众包和竞争等社会联系提供支持的数字经济中。
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.
