CIF: Small: Intervention: A Design Framework for Resource Sharing and Exchanges Among Self-interested Users

在非合作的资源共享与交换系统中，用户为了优化各自的目标而竞争可用的资源。从系统设计者的角度来看，自利用户的操作通常会导致次优性能。本研究涉及开发一种新的激励设计框架的资源共享和交换系统，设计者可以完美或不完美地监控自利用户的行为，并干预他们的互动。研究人员系统地研究了设计者可以通过设计合适的协议来提高各种非合作网络和系统的性能，以及如何实现这些改进，因为它有能力监控用户并进行干预。本研究制定并解决了设计师的问题，找到一个最佳的干预规则，优化设计师的目标，同时明确考虑用户的自私性质。所获得的结果的特点在何种程度上，设计师可以塑造用户的激励取决于它的能力，以监测用户的行为，并影响用户的收益。研究人员系统地研究了多用户交互场景，其中用户偶尔交互，这将被建模为具有干预的一次性游戏，以及用户建立长期关系的情况，这将被建模为具有干预的重复游戏。在这两种情况下，完美和不完美的用户监控的情况下？行动将被调查。总的来说，这项研究提供了一个新的框架，以评估具有监测和干预能力的设计师的性能增益，并找出利用其能力的最佳方式。

In non-cooperative resource sharing and exchange systems, users compete for available resources aiming to optimize their individual objectives. Operation by self-interested users often results in suboptimal performance from a system designer's point of view. This research involves the development of a new incentive design framework for resource sharing and exchange systems where the designer can perfectly or imperfectly monitor the actions of self-interested users and intervene in their interaction. The investigators systematically study what the designer can achieve in terms of improving the performance of various non-cooperative networks and systems by designing suitable protocols and how it can achieve these improvements, given its abilities to monitor the users and its capability to intervene. This research formulates and solves the designer's problem of finding an optimal intervention rule that optimizes the designer's objective while explicitly considering the selfish nature of users. The results obtained characterize the extent to which the designer can shape the incentives of users depending on its ability to monitor the actions of users and to impact the payoffs of users. The investigators systematically study both multi-user interactions scenarios where the users interact sporadically, which will be modeled as one-shot games with intervention, as well as the case where users establish long-term relationships, which will be modeled as repeated games with intervention. In both scenarios, the cases of perfect and imperfect monitoring of the users? actions will be investigated. Overall, this research provides a novel framework to evaluate the performance gain from having a designer that has a monitoring and intervention ability, and to figure out the best way to utilize its capabilities.