论文标题
网络多代理系统中线性解决的最佳控制的组成性
Compositionality of Linearly Solvable Optimal Control in Networked Multi-Agent Systems
论文作者
论文摘要
在本文中，我们通过使用线性解决的最佳控制（LSOC）问题的线性组成原理（LSOC）问题讨论了从学习的组件任务中概括最佳控制定律的方法。所提出的方法以离散时间和连续时间的方式以样本效率的方式同时实现了控制动作的组成性和最佳性，这减少了质量新任务的最佳控制解决方案的重新计算负担。我们研究了所提出的方法在MAS上的应用，并通过代理之间的协调性进行了协调。该实验在研究的方案中显示出可行的结果，包括无需重新采样的任务概括的离散和连续动力学系统。
In this paper, we discuss the methodology of generalizing the optimal control law from learned component tasks to unlearned composite tasks on Multi-Agent Systems (MASs), by using the linearity composition principle of linearly solvable optimal control (LSOC) problems. The proposed approach achieves both the compositionality and optimality of control actions simultaneously within the cooperative MAS framework in both discrete- and continuous-time in a sample-efficient manner, which reduces the burden of re-computation of the optimal control solutions for the new task on the MASs. We investigate the application of the proposed approach on the MAS with coordination between agents. The experiments show feasible results in investigated scenarios, including both discrete and continuous dynamical systems for task generalization without resampling.
