œ-Boids基于自适应群集模型的共识算法

M. Gulzar, Muhammad Munawar, Javaria Khalil, Daud Sibtain, Adeel Ahmed
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引用次数: 4

摘要

多智能体群集是指通过相互作用来实现一些共同的群体目标。本文采用自适应群集模型实现多智能体的一致性。利用该模型,可以通过随机选择agent的初始位置和速度来实现共识。此外,通过使用不同的图拓扑,对7个agent (N= 7)的仿真结果进行了演示,以保证agent在不同迭代时的平均速度、位置和方向的收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
œ-Boids Consensus Algorithm using Adaptive Flocking Model
Multi-agent flocking means to achieve some common group objectives by interacting with each other. In this paper, an adaptive flocking model is implemented to achieve the consensus of multi-agents. By using this model, consensus can be implemented by randomly choosing the initial positions and velocities of the agents. Moreover, by using different graph topologies, the simulation results for 7 agents (N= 7) are demonstrated to ensure the convergence of the agent's average velocity, positions and directions at different iterations.
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