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

机译:基于MAX流量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:多代理系统文献中的组织模型具有静态性质。根据组织模型的适应的情况对于确保系统的连续成功功能至关重要。本文介绍了一种基于MAX流量网络的方法,以动态调整组织模型以环境波动。首先,提出了众所周知的组织建模框架和最大流量网络之间的正式映射。具有这样的映射维持组织模型的富有洞察力的结构,而基于MAX流量网络也可以指定有效的适应算法。此后,基于MAX流量网络的两个适配机制被引入每个适合于不同的环境特征。

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