论文标题
有限的置信动力学和图形控制：执行共识
Bounded confidence dynamics and graph control: enforcing consensus
论文作者
论文摘要
有限置信类型模型的一个通用特征是形成了代理簇。我们提出和研究有界置信动力学的变体，目的是诱导无条件收敛到共识。这些动力学的定义特征，我们将其命名为“没有人”的动力学，这是对代理的局部控制的引入，从而保留了交互网络的连通性。我们严格地表明，这些动力学导致无条件的收敛到共识。我们论点的定性性质阻止了我们量化共识的速度，但是我们提供了数值证据，表明急剧收敛速率对于这种动态而言将具有挑战性。最后，我们提出了一个放松的控件版本。随着控件仍然维持相互作用网络的连通性，结果保持有限置信动力学的许多定性特征，但最终仍融合了共识。
A generic feature of bounded confidence type models is the formation of clusters of agents. We propose and study a variant of bounded confidence dynamics with the goal of inducing unconditional convergence to a consensus. The defining feature of these dynamics, which we name the No one left behind dynamics, is the introduction of a local control on the agents which preserves the connectivity of the interaction network. We rigorously demonstrate that these dynamics result in unconditional convergence to a consensus. The qualitative nature of our argument prevents us quantifying how fast a consensus emerges, however we present numerical evidence that sharp convergence rates would be challenging to obtain for such dynamics. Finally, we propose a relaxed version of the control. The dynamics that result maintain many of the qualitative features of the bounded confidence dynamics yet ultimately still converge to a consensus as the control still maintains connectivity of the interaction network.
