Beyond Independent Manipulation: Individual Fairness-aware Strategic Classification with Peer Imitation
超越独立操纵:具有同伴模仿的个体公平感知策略分类
机构 * College of Computer Science and Technology, National University of Defense Technology(国防科技大学计算机科学与技术学院) ; School of Mathematical Sciences, Peking University(北京大学数学学院) ; Institute for Theoretical Computer Science, Shanghai University of Finance and Economics(上海财经大学理论计算机科学研究所) ; Information Technology Development, Aetos Capital Group, Sydney(悉尼Aetos资本集团信息技术部) ; Faculty of Computing, Harbin Institute of Technology(哈尔滨工业大学计算机学院) ; Department of Computer Science and Technology, Tsinghua University(清华大学计算机科学与技术系)
AI总结 提出个体公平感知策略分类(IFSC)框架,通过建模基于个体公平的同伴驱动操纵(模仿邻近被接受同伴),并采用鲁棒学习过程处理同伴可观测性不确定性,以改善个体公平一致性并减轻模仿引起的扭曲。
Comments Accepted by SIGKDD2026