Eliminating Public Knowledge Biases in Information-Aggregation Mechanisms
提出一种新方法，通过信息市场和协调博弈两阶段机制，识别并消除小群体信息聚合中的公共知识偏差，实验表明非线性聚合优于不完美市场和最佳参与者。
We present a novel methodology for identifying public knowledge and eliminating the biases it creates when aggregating information in small group settings. A two-stage mechanism consisting of an information market and a coordination game is used to reveal and adjust for individuals' public information. A nonlinear aggregation of their decisions then allows for the calculation of the probability of the future outcome of an uncertain event, which can then be compared to both the objective probability of its occurrence and the performance of the market as a whole. Experiments show that this nonlinear aggregation mechanism outperforms both the imperfect market and the best of the participants.