资源配置中的福利测度：超越平均与最大最小
Welfare Measure for Resource Allocation with Algorithmic Implementation: Beyond Average and Max-Min
摘要：
在这项工作中，我们提出了一个公理化的方法来衡量的性能/福利的系统组成的并发代理在资源驱动的系统。我们的方法提供了一个统一的观点流行的系统最优性原则，如最大平均/总效用和最大最小公平性。此外，它还产生了其他尚未充分利用的系统最优性概念，如最大最低总子群效用。对于公理化定义的福利测度，我们提供了一个通用的基于梯度的方法来寻找最优的资源配置，并提出了一个理论保证其成功。最后，我们通过无线网络中的功率控制应用程序展示了我们的方法的力量。
英文摘要：
In this work, we propose an axiomatic approach for measuring the performance/welfare of a system consisting of concurrent agents in a resource-driven system. Our approach provides a unifying view on popular system optimality principles, such as the maximal average/total utilities and the max-min fairness. Moreover, it gives rise to other system optimality notions that have not been fully exploited yet, such as the maximal lowest total subgroup utilities. For the axiomatically defined welfare measures, we provide a generic gradient-based method to find an optimal resource allocation and present a theoretical guarantee for its success. Lastly, we demonstrate the power of our approach through the power control application in wireless networks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
