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Adaptation of Organizational Models for Multi-Agent Systems based on Max Flow Networks

机译:基于最大流网络的多代理系统组织模型适应

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Organizational models within multi-agent systems literature are of a static nature. Depending upon circumstances adaptation of the organizational model can be essential to ensure a continuous successful function of the system. This paper presents an approach based on max flow networks to dynamically adapt organizational models to environmental fluctuation. First, a formal mapping between a well-known organizational modeling framework and max flow networks is presented. Having such a mapping maintains the insightful structure of an organizational model whereas specifying efficient adaptation algorithms based on max flow networks can be done as well. Thereafter two adaptation mechanisms based on max flow networks are introduced each being appropriate for different environmental characteristics.
机译:多主体系统文献中的组织模型具有静态性质。根据情况的不同,组织模型的适应对于确保系统的连续成功运行至关重要。本文提出了一种基于最大流量网络的方法,可以动态地使组织模型适应环境波动。首先,介绍了著名的组织建模框架和最大流量网络之间的形式映射。拥有这种映射关系可以维护组织模型的深刻见解,同时也可以基于最大流量网络指定有效的自适应算法。此后,引入了基于最大流量网络的两种适应机制,每种机制都适合于不同的环境特征。

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