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Matching Dynamics with Constraints

机译:约束条件匹配动力学

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We study uncoordinated matching markets with additional local constraints that capture, e.g., restricted information, visibility, or externalities in markets. Each agent is a node in a fixed matching network and strives to be matched to another agent. Each agent has a complete preference list over all other agents it can be matched with. However, depending on the constraints and the current state of the game, not all possible partners are available for matching at all times. For correlated preferences, we propose and study a general class of he-donic coalition formation games that we call coalition formation games with constraints. This class includes and extends many recently studied variants of stable matching, such as locally stable matching, socially stable matching, or friendship matching. Perhaps surprisingly, we show that all these variants are encompassed in a class of "consistent" instances that always allow a polynomial improvement sequence to a stable state. In addition, we show that for consistent instances there always exists a polynomial sequence to every reachable state. Our characterization is tight in the sense that we provide exponential lower bounds when each of the requirements for consistency is violated. We also analyze matching with uncorrelated preferences, where we obtain a larger variety of results. While socially stable matching always allows a polynomial sequence to a stable state, for other classes different additional assumptions are sufficient to guarantee the same results. For the problem of reaching a given stable state, we show NP-hardness in almost all considered classes of matching games.
机译:我们研究具有其他局限性的不协调匹配市场,这些局限性捕获(例如)有限的信息,可见性或市场外部性。每个代理都是固定匹配网络中的一个节点,并努力与另一个代理进行匹配。每个代理都有一个与其可以匹配的所有其他代理完整的首选项列表。但是,取决于约束条件和游戏的当前状态,并非所有可能的合作伙伴始终都可用于匹配。对于相关的偏好,我们提出并研究了一般的hedonic联盟形成博弈,我们将其称为具有约束条件的联盟形成博弈。该课程包括并扩展了许多最近研究的稳定匹配的变体,例如本地稳定匹配,社会稳定匹配或友谊匹配。也许令人惊讶的是,我们表明所有这些变体都包含在一类“一致”的实例中,这些实例始终允许多项式改进序列达到稳定状态。另外,我们表明,对于一致的实例,对于每个可达状态始终存在一个多项式序列。从严格意义上来说,我们的表征是严格的,当违反一致性要求时,我们提供指数下限。我们还会分析具有不相关偏好的匹配,从而获得更多结果。尽管社会稳定的匹配总是允许多项式序列达到稳定的状态,但对于其他类别,不同的附加假设足以保证相同的结果。对于达到给定稳定状态的问题,我们在几乎所有考虑到的匹配游戏类中都显示了NP硬度。

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