This paper studies the optimal cooperative output regulation problem for unknown linear multi-agent systems by the integral reinforcement learning technique. Existing results on this problem were obtained by a non-fully distributed learning process. In contrast, we propose a distributed learning algorithm over the jointly connected switching communication networks. Moreover, by modifying the existing algorithm, we reduce the computational cost and weaken the solvability conditions. Two numerical examples are used to illustrate the effectiveness of our approach.

中文翻译：

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通过积分强化学习的分布式自适应协作最优输出调节


本文利用积分强化学习技术研究未知线性多智能体系统的最优协作输出调节问题。该问题的现有结果是通过非完全分布式学习过程获得的。相反，我们提出了一种在联合连接的交换通信网络上的分布式学习算法。此外，通过修改现有算法，我们降低了计算成本并削弱了可解性条件。使用两个数值示例来说明我们方法的有效性。