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Efficient Search of Relevant Structures in Complex Systems

机译:在复杂系统中有效搜索相关结构

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In a previous work, Villani et al. introduced a method to identify candidate emergent dynamical structures in complex systems. Such a method detects subsets (clusters) of the system elements which behave in a coherent and coordinated way while loosely interacting with the remainder of the system. Such clusters are assessed in terms of an index that can be associated to each subset, called Dynamical Cluster Index (DCI). When large systems are analyzed, the "curse of dimensionality" makes it impossible to compute the DCI for every possible cluster, even using massively parallel hardware such as GPUs. In this paper, we propose an efficient metaheuristic for searching relevant dynamical structures, which hybridizes an evolutionary algorithm with local search and obtains results comparable to an exhaustive search in a much shorter time. The effectiveness of the method we propose has been evaluated on a set of Boolean models of real-world systems.
机译:在先前的工作中,维拉尼等人。介绍了一种在复杂系统中识别候选紧急动态结构的方法。这种方法检测系统元素的子集(簇),这些子集以连贯和协调的方式运行,同时与系统的其余部分进行松散的交互。根据可以与每个子集相关联的索引(称为动态群集索引(DCI))评估此类群集。在分析大型系统时,“维数诅咒”使得即使使用诸如GPU之类的大规模并行硬件,也无法为每个可能的群集计算DCI。在本文中,我们提出了一种用于搜索相关动力学结构的有效元启发式算法,该算法将进化算法与局部搜索进行了混合,并在更短的时间内获得了与穷举搜索相当的结果。我们提出的方法的有效性已在一组真实系统的布尔模型上进行了评估。

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