Eliciting Informative Feedback: The Peer-Prediction Method
设计了一种评分系统，通过让评分者报告信号并基于对他人报告的推断后验概率应用评分规则，激励诚实反馈，并证明诚实报告是纳什均衡。适用于学术评审和在线推荐系统等场景。
Many recommendation and decision processes depend on eliciting evaluations of opportunities, products, and vendors. A scoring system is devised that induces honest reporting of feedback. Each rater merely reports a signal, and the system applies proper scoring rules to the implied posterior beliefs about another rater’s report. Honest reporting proves to be a Nash equilibrium. The scoring schemes can be scaled to induce appropriate effort by raters and can be extended to handle sequential interaction and continuous signals. We also address a number of practical implementation issues that arise in settings such as academic reviewing and online recommender and reputation systems.