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通过智能代理对多智能体系统进行无损干预。

Nondestructive intervention to multi-agent systems through an intelligent agent.

机构信息

Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.

出版信息

PLoS One. 2013 May 2;8(5):e61542. doi: 10.1371/journal.pone.0061542. Print 2013.

Abstract

For a given multi-agent system where the local interaction rule of the existing agents can not be re-designed, one way to intervene the collective behavior of the system is to add one or a few special agents into the group which are still treated as normal agents by the existing ones. We study how to lead a Vicsek-like flocking model to reach synchronization by adding special agents. A popular method is to add some simple leaders (fixed-headings agents). However, we add one intelligent agent, called 'shill', which uses online feedback information of the group to decide the shill's moving direction at each step. A novel strategy for the shill to coordinate the group is proposed. It is strictly proved that a shill with this strategy and a limited speed can synchronize every agent in the group. The computer simulations show the effectiveness of this strategy in different scenarios, including different group sizes, shill speed, and with or without noise. Compared to the method of adding some fixed-heading leaders, our method can guarantee synchronization for any initial configuration in the deterministic scenario and improve the synchronization level significantly in low density groups, or model with noise. This suggests the advantage and power of feedback information in intervention of collective behavior.

摘要

对于一个给定的多智能体系统,其中现有智能体的局部交互规则无法重新设计,干预系统集体行为的一种方法是向群体中添加一个或几个特殊智能体,这些智能体仍然被现有智能体视为正常智能体。我们研究如何通过添加特殊智能体来引导类似 Vicsek 的群体达到同步。一种流行的方法是添加一些简单的领导者(固定头部智能体)。然而,我们添加了一个智能体,称为“卧底”,它使用群体的在线反馈信息来决定卧底在每一步的移动方向。提出了一种卧底协调群体的新策略。严格证明了具有此策略和有限速度的卧底可以使群体中的每个智能体同步。计算机模拟显示了该策略在不同场景下的有效性,包括不同的群体规模、卧底速度以及是否存在噪声。与添加一些固定头部领导者的方法相比,我们的方法可以在确定性场景中保证任何初始配置的同步,并在低密度群体或噪声模型中显著提高同步水平。这表明反馈信息在干预集体行为方面的优势和力量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ea0a/3642172/42d8a587476e/pone.0061542.g001.jpg

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