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Swarm controlled emergence for ant clustering

机译:群控制出现的蚂蚁聚类

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Purpose - Swarm controlled emergence is proposed as an approach to control emergent effects in (artificial) swarms. The method involves the introduction of specific control agents into the swarm systems. Control agents behave similar to the normal agents and do not directly influence the behavior of the normal agents. The specific design of the control agents depends on the particular swarm system considered. The aim of this paper is to apply the method to ant clustering. Ant clustering, as an emergent effect, can be observed in nature and has inspired the design of several technical systems, e.g. moving robots, and clustering algorithms. Design/methodology/approach - Different types of control agents for that ant clustering model are designed by introducing slight changes to the behavioural rules of the normal agents. The clustering behaviour of the resulting swarms is investigated by extensive simulation studies. Findings - It is shown that complex behavior can emerge in systems with two types of agents (normal agents and control agents). For a particular behavior of the control agents, an interesting swarm size dependent effect was found. The behaviour prevents clustering when the number of control agents is large, but leads to stronger clustering when the number of control agents is relatively small. Research limitations/implications - Although swarm controlled emergence is a general approach, in the experiments of this paper the authors concentrate mainly on ant clustering. It remains for future research to investigate the application of the method in other swarm systems. Swarm controlled emergence might be applied to control emergent effects in computing systems that consist of many autonomous components which make decentralized decisions based on local information. Practical implications - The particular finding, that certain behaviours of control agents can lead to stronger clustering, can help to design improved clustering algorithms by using heterogeneous swarms of agents. Originality/value - In general, the control of (unwanted) emergent effects in artificial systems is an important problem. However, to date not much research has been done on this topic. This paper proposes a new approach and opens a different research direction towards future control principles for self-organized systems that consist of a large number of autonomous components.
机译:目的-提出了群体控制的涌现作为一种控制(人工)群体中涌现效应的方法。该方法包括将特定的控制剂引入群体系统。对照剂的行为与正常剂相似,并且不直接影响正常剂的行为。控制代理的具体设计取决于所考虑的特定群体系统。本文的目的是将该方法应用于蚂蚁聚类。在自然界中可以观察到蚂蚁群集的出现,并激发了一些技术系统的设计,例如移动机器人和聚类算法。设计/方法/方法-通过对正常代理的行为规则进行细微更改来设计用于该蚂蚁聚类模型的不同类型的控制代理。通过广泛的模拟研究来研究所得群体的聚类行为。研究结果-结果表明,在具有两种类型的代理(正常代理和控制代理)的系统中会出现复杂的行为。对于控制剂的特定行为,发现了有趣的群大小依赖性效应。当控制代理的数量较大时,此行为可防止群集,但当控制代理的数量相对较小时,则可导致更强的群集。研究的局限性/意义-尽管群体控制的出现是一种通用方法,但在本文的实验中,作者主要集中于蚂蚁聚类。研究该方法在其他群体系统中的应用还有待进一步研究。群控制紧急情况可能会应用于控制计算机系统中的紧急情况,该计算机系统由许多自治组件组成,这些组件会根据本地信息做出分散决策。实际意义-特定发现,即控制代理的某些行为可以导致更强的聚类,可以通过使用不同种类的代理来帮助设计改进的聚类算法。原创性/价值-通常,在人工系统中控制(不需要的)紧急效果是一个重要的问题。但是,迄今为止,关于该主题的研究还很少。本文提出了一种新方法,并为包含大量自治组件的自组织系统的未来控制原理打开了不同的研究方向。

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