Robustness in Mechanism Design and Contracting
这篇综述总结了当设计者不完全了解环境时如何设计激励的理论研究，提供了基于不确定性和稳健性的新工具，补充了传统贝叶斯方法，拓宽了可研究问题的范围。
This review summarizes a nascent body of theoretical research on design of incentives when the environment is not fully known to the designer and offers some general lessons from the work so far. These recent models based on uncertainty and robustness offer an additional set of tools in the toolkit, complementary to more traditional, fully Bayesian modeling approaches, and broaden the range of problems that can be studied. The kinds of insights that such models can offer, and the methodological and technical challenges that they confront, broadly parallel those of traditional approaches.