Randomized mechanisms can have good normative properties compared to their deterministic counterparts. However, randomized mechanisms are problematic in several ways such as in their verifiability. We propose here to derandomize such mechanisms by having agents play a game instead of tossing a coin. The game is designed so an agent's best action is to play randomly, and this play then injects ``randomness'' into the mechanism. This derandomization retains many of the good normative properties of the original randomized mechanism but gives a mechanism that is deterministic and easy, for instance, to audit. We consider three related methods to derandomize randomized mechanism in six different domains: voting, facility location, task allocation, school choice, peer selection, and resource allocation. We propose a number of novel derandomized mechanisms for these six domains with good normative properties. Each mechanism has a mixed Nash equilibrium in which agents play a modular arithmetic game with an uniform mixed strategy. In all but one mixed Nash equilibrium, agents report their preferences over the original problem sincerely. The derandomized methods are thus ``quasi-strategy proof''. In one domain, we additionally show that a new and desirable normative property emerges as a result of derandomization.

随机化机制具有比确定性对应物更好的规范性质，但是随机化机制存在可验证性等问题。我们提出了通过让代理人玩游戏而不是抛硬币来解决此类机制的问题。这种游戏设计使得代理人最佳行动是随机玩，从而将“随机性”注入机制。这种去随机化保留了原始随机化机制的许多良好规范特性，但是提供了一种确定性且易于审核的机制。我们考虑了六个不同领域的随机化机制去随机化的三种相关方法：投票、设施选址、任务分配、学校选择、同行选择和资源分配。我们为这六个领域提出了许多具有良好规范性质的新型去随机化机制。每种机制都具有一个均匀混合策略的模块算术游戏的混合纳什均衡。除了一个混合纳什均衡外，代理人以真诚的方式报告了他们对原始问题的偏好。因此，这些去随机化方法是“准策略证明的”。在一个领域中，我们还展示了由于去随机化而产生了新的理想规范性质。

玩游戏而非抛硬币的机制