In applications such as participatory sensing and crowd sensing, self-interested agents exert costly effort towards achieving an objective for the system operator. We study such a setup where a principal incentivizes multiple agents of different types who can collude with each other to derive rent. The principal cannot observe the efforts exerted directly, but only the outcome of the task, which is a noisy function of the effort. The type of each agent influences the effort cost and task output. For a duopoly in which agents are coupled in their payments, we show that if the principal and the agents interact finitely many times, the agents can derive rent by colluding even if the principal knows the types of the agents. However, if the principal and the agents interact infinitely often, the principal can disincentivize agent collusion through a suitable data-driven contract.

中文翻译：

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具有共谋检测的多代理系统的数据驱动合同设计

在诸如参与感测和人群感测之类的应用中，自私的代理人为实现系统操作员的目标付出了巨大的努力。我们研究了这样一种设置，即委托人激励多个不同类型的代理人，他们可以相互勾结以获取租金。委托人不能观察直接施加的努力，而只能观察任务的结果，这是努力的嘈杂功能。每个代理的类型都会影响工作量成本和任务输出。对于将代理人与他们的付款耦合在一起的双头垄断，我们表明，如果委托人和代理人有限地相互作用多次，即使委托人知道代理人的类型，代理人也可以通过勾结来获得租金。但是，如果委托人和代理人之间经常无限地互动，