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ON THE ROLE OF HOMOGENEITY WHEN CONTROLLING SINGLE-LEADER NETWORKS

机译:均质性在控制单层网络中的作用

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This paper presents an approach to controlling agent positions in single-leader networks to target points while explicitly taking agent homogeneity into account. When the capabilities of agents to accomplish tasks at each of the targets are identical, then the label of the target points may be permuted while still expressing the same intention. In single-leader networks which are not completely controllable, such a permutation of the target points may at times move a target closer to the system's reachable subspace, thereby allowing the network to surpass the limitations on controllability when homogeneity is not considered explicitly. To fully exploit this property in homogeneous networks, it is then necessary to find the permutation of a target point which brings it closest to the reachable subspace. However, finding this optimal permutation is shown to be in general a non-deterministic polynomial-time (NP)-hard problem. Specific network topologies are identified for when finding such an optimal permutation of a target point can be advantageous when controlling single-leader networks. Moreover, an alternate view of the problem of finding optimal permutations is presented in which clustering-based algorithms can be applied to find suboptimal solutions.
机译:本文提出了一种在单领导者网络中控制座席位置以控制目标点的方法,同时明确考虑了座席同质性。当代理在每个目标上完成任务的能力相同时,可以对目标点的标签进行置换,同时仍然表达相同的意图。在并非完全可控的单头网络中,目标点的这种排列有时可能会使目标移近系统的可到达子空间,从而在未明确考虑同质性时允许网络超越可控制性的限制。为了在同类网络中充分利用此属性,必须找到目标点的置换,使其最接近可到达子空间。但是,发现找到最佳排列通常显示为不确定的多项式时间(NP)难题。当发现目标点的这种最佳排列时,识别特定的网络拓扑对于控制单领导者网络可能是有利的。此外,提出了寻找最佳置换问题的另一种观点,其中基于聚类的算法可用于寻找次优解决方案。

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