论文标题
开放多代理系统中的资源分配：在线优化分析
Resource allocation in open multi-agent systems: an online optimization analysis
论文作者
论文摘要
资源分配问题包括组中代理之间预算的最佳分配。我们在开放系统的背景下考虑了这样一个问题，在某些时间实例中可以更换代理。这些替代者会导致预算和总成本功能的变化，从而阻碍了整个网络的性能。对于简单的设置，我们使用类似于在线优化中常用的工具分析了随机坐标下降算法（RCD）的性能。特别是，我们研究了比较从RCD算法和最佳解决方案或非批准自私策略比较解决方案的累积错误，并且我们对这些累积错误的预期得出了一些界限。
The resource allocation problem consists of the optimal distribution of a budget between agents in a group. We consider such a problem in the context of open systems, where agents can be replaced at some time instances. These replacements lead to variations in both the budget and the total cost function that hinder the overall network's performance. For a simple setting, we analyze the performance of the Random Coordinate Descent algorithm (RCD) using tools similar to those commonly used in online optimization. In particular, we study the accumulated errors that compare solutions issued from the RCD algorithm and the optimal solution or the non-collaborating selfish strategy and we derive some bounds in expectation for these accumulated errors.
