Community-based Informed Agents Selection for Flocking with a Virtual Leader
Nuwan Ganganath*, Chi-Tsun Cheng, Xiaofan Wang, and Chi K. Tse
International Journal of Control, Automation, and Systems, vol. 15, no. 1, pp.394-403, 2017
Abstract : "It has been studied that a few informed individuals in a group of interacting dynamic agents can influence
the majority to follow the position and velocity of a virtual leader. Previously it has been shown that a cluster-based
selection of informed agents can drive more agents to follow the virtual leader compared to a random selection.
However, a practical question is: How many informed agents to select? In order to address this, here we propose
a novel method for selecting informed agents based on community structures in the initial spatial distribution of
agents. The number of informed agents are decided based on the strongest community structure. We test and
analyze the performance of the proposed method against random and cluster-based selections of informed agents
using extensive computer simulations. Results of our study show that community-based selection can be useful
in deciding an optimum number of informed agents such that a majority of the group can achieve their common
objective."
Keyword : Communities, controllability, flocking, informed agents, virtual leader. |