Improving algorithms via predictions is a very active research topic in recent years. This paper initiates the systematic study of mechanism design in this model. In a number of well-studied mechanism design settings, we make use of imperfect predictions to design mechanisms that perform much better than traditional mechanisms if the predictions are accurate (consistency), while always retaining worst-case guarantees even with very imprecise predictions (robustness). Furthermore, we refer to the largest prediction error sufficient to give a good performance as the error tolerance of a mechanism, and observe that an intrinsic tradeoff among consistency, robustness and error tolerance is common for mechanism design with predictions.

翻译：通过预测改进算法是近年来一个非常积极的研究课题。本文件提出对这一模型的机制设计进行系统研究。在一些研究周密的机制设计设置中,我们利用不完善的预测设计出机制,如果预测准确(一致性),则其效果好于传统机制,同时始终保留最坏情况的保证,即使预测非常不精确(强力 ) 。此外,我们提到最大的预测误差足以使良好的性能成为机制的误差容忍度,并指出一致性、稳健性和误差容忍度之间的内在权衡对于有预测的机制设计是常见的。