论文标题
不平等限制的在线分散决策：ADMM方法
Online decentralized decision making with inequality constraints: an ADMM approach
论文作者
论文摘要
我们讨论了一个在线分散的决策问题，其中代理与仿射不平等约束相结合。乘数的交替方向方法（ADMM）用作计算引擎，我们在在线环境中讨论算法的收敛性。要具体来说，当必须按固定的时间步长依次做出决策时，在方案更改之前，ADMM可能没有足够的时间收敛，并且需要更新决策。在这种情况下，采用了次优的解决方案，我们分析了鉴于收敛条件的最佳差距。而且，在许多情况下，决策问题随着时间的推移逐渐改变。我们提出了一个温暖的启动计划，以加速ADMM的融合并分析温暖启动的好处。该方法在模拟的分散多基因控制屏障功能问题中证明了该方法。
We discuss an online decentralized decision making problem where the agents are coupled with affine inequality constraints. Alternating Direction Method of Multipliers (ADMM) is used as the computation engine and we discuss the convergence of the algorithm in an online setting. To be specific, when decisions have to be made sequentially with a fixed time step, there might not be enough time for the ADMM to converge before the scenario changes and the decision needs to be updated. In this case, a suboptimal solution is employed and we analyze the optimality gap given the convergence condition. Moreover, in many cases, the decision making problem changes gradually over time. We propose a warm-start scheme to accelerate the convergence of ADMM and analyze the benefit of the warm-start. The proposed method is demonstrated in a decentralized multiagent control barrier function problem with simulation.
