Approximation in Mechanism Design
探讨机制设计面临的三个挑战：最优机制对偏好分布细节敏感、多维偏好下缺乏一般性刻画、以及需要不现实的分布知识，并综述了近似方法如何解决这些问题，对理论和实践均有参考价值。
This paper considers three challenge areas for mechanism design and describes the role approximation plays in resolving them. Challenge 1: optimal mechanisms are finely tuned to precise details of the distribution on agent preferences. Challenge 2: in environments with multi-dimensional agent preferences economic analysis has failed to provide general characterizations optimal mechanisms. Challenge 3: optimal mechanisms are parameterized by unrealistic knowledge of the distribution of agents' private preferences. This paper surveys positive resolutions to these challenges with emphasis on basic techniques and their relevance to theory and practice.