论文标题
交易网络的机制学习
Mechanism Learning for Trading Networks
论文作者
论文摘要
我们研究了满足四个期望特性的交易网络设计机制的问题：主要策略激励措施兼容性，效率，预算余额疲软（WBB）和个人合理性（IR）。尽管存在同时满足组合拍卖的这些属性的机制，但我们证明了不可能在广泛的交易网络中存在这种机制。因此，我们提出了计算和学习满足四种特性的机制的方法，在贝叶斯环境中，WBB和IR分别放宽了以前和临时。对于计算和样本效率，我们介绍了几种技术，包括游戏理论分析以减少输入特征空间。我们从经验上证明，所提出的方法成功地找到了不可能存在的交易网络的四个特性的机制。
We study the problem of designing mechanisms for trading networks that satisfy four desired properties: dominant-strategy incentive compatibility, efficiency, weak budget balance (WBB), and individual rationality (IR). Although there exist mechanisms that simultaneously satisfy these properties ex post for combinatorial auctions, we prove the impossibility that such mechanisms do not exist for a broad class of trading networks. We thus propose approaches for computing and learning the mechanisms that satisfy the four properties, in a Bayesian setting, where WBB and IR, respectively, are relaxed to ex ante and interim. For computational and sample efficiency, we introduce several techniques, including game theoretical analysis to reduce the input feature space. We empirically demonstrate that the proposed approaches successfully find the mechanisms with the four properties for those trading networks where the impossibility holds ex post.
