发表机构
Thayer Department of Engineering, Dartmouth College; Computer Science Department, University of Colorado Colorado Springs（达特茅斯学院塞耶工程学院; 科罗拉多大学科泉分校计算机科学系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究针对通信受限环境下的资源分配博弈，提出计算最小通信网络的高效算法，确保与完全信息情况相同的性能保证，并提供纳什均衡计算及严格纳什均衡存在性条件。
AI 中文摘要
越来越多地，资源分配博弈被提出来模拟通信受限环境中的团队协调。特别关注的是理解通信受限对涌现团队协调质量的影响。在本工作中，我们考虑具有任意通信网络的情况，并使用无政府代价（Price of Anarchy）来量化涌现行为的质量。我们的主要结果是一个计算高效的算法，该算法计算出一个最小通信网络，其性能保证与完全信息情况相同。此外，我们提供了在完全信息设置下计算纳什均衡和严格纳什均衡的高效算法。最后，为支持这些算法，我们提供了严格纳什均衡存在的充分条件，刻画了所有通信网络中的严格纳什均衡，并表明完全信息情况下的每个严格纳什均衡都有一个必要且充分的通信链路集合来诱导它。我们通过所提算法的执行时间实验和若干示例博弈的检验来结束本文。
英文摘要
Increasingly, resource allocation games are being proposed to model team coordination in denied communication environments. Of particular interest is understanding the impact of communication denial on the quality of emergent team coordination. In this work, we consider the situation with an arbitrary communication network and use the Price of Anarchy to quantify the quality of emergent behavior. Our main result is a computationally efficient algorithm that calculates a minimal communication network that has the same performance guarantee as the full information case. Additionally, we provide efficient algorithms that compute a Nash and a strict Nash equilibrium in the full information setting. Finally to support these algorithms, we provide sufficient conditions for the existence of a strict Nash equilibrium, characterize strict Nash equilibria across all communication networks, and show that each strict Nash equilibrium in the full information case has a necessary and sufficient set of communication links that induce it. We conclude by giving an execution time experiment of the proposed algorithm and examine several example games.
