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A Novel Metric for Comparing the Intelligence of Two Swarm Multiagent Systems

机译:比较两个群体多智能体系统智能的新指标

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Background: Swarm systems are used for many difficult, even NP-hard problems solving. In the scientific literature, the swarm systems intelligence is mostly considered at the swarm level and it is based on some considerations, like autonomous learning, self-adaptation, evolution and efficient and flexible problems solving. It were identified as a necessity the elaboration of metrics that allow an effective and accurate measuring of swarm systems intelligence, taking also into consideration the variability of intelligence in the systems responses to different situations. Materials and Methods: In this study a novel metric, called MetrInt have been proposed for accurate comparison of two swarm systems intelligence. For proving the effectiveness of the metric, it was realized a case study for two swarm systems that mimic the biological ant colony, which solve a computational NP-hard problem, the traveling salesman problem. Results: The main result reported in this study consists in the proposed metric for comparison of two swarm systems intelligence. By applying the proposed metric, MetrInt, in the case study, it resulted that the two studied swarm multiagent systems can be considered as having the same intelligence level even there is a measurable numerical difference in intelligence. Based on this consideration, it can be concluded that both of them can be included in the same intelligence class. Conclusion: The proposed metric is appropriate for comparing two swarm systems with the same type of intelligence based on their intelligence level. It is also appropriate in the case of the design of swarm systems that should intelligently solve problems. The proposed metric is appropriate for comparison of two swarm systems intelligence. A swarm system could behave in different situations with lower or higher intelligence. MetrInt is an accurate metric, which takes into consideration the intelligence manifestation?s variability. It is effective even in the case of small differences in the intelligence of the swarm systems. Two swarm systems with the same intelligence level could be considered that belong to the same intelligence class.
机译:背景技术:群体系统用于解决许多困难的问题,甚至解决NP难题。在科学文献中,群体系统智能主要是在群体层次上考虑的,它基于一些考虑因素,例如自主学习,自适应,进化以及高效灵活的问题解决方法。确定必须制定能够有效,准确地测量群体系统智能的度量标准,同时还要考虑系统对不同情况的响应中智能的可变性。材料和方法:在这项研究中,提出了一种称为MetrInt的新颖度量标准,用于准确比较两个群体系统的智能。为了证明该指标的有效性,针对两个模仿生物蚁群的群体系统进行了案例研究,解决了计算NP难问题,即旅行商问题。结果:本研究报告的主要结果包括用于比较两个群体系统智能的拟议指标。通过在案例研究中应用拟议的度量标准MetrInt,结果是,即使在智能方面存在可测量的数值差异,两个研究的群体多智能体系统也可以被视为具有相同的智能级别。基于此考虑,可以得出结论,两者都可以包含在同一情报类别中。结论:建议的度量标准适合于根据智能水平比较具有相同类型智能的两个群体系统。在设计应该智能解决问题的群体系统的情况下,这也是合适的。提出的度量标准适合比较两个群体系统的智能。群体系统可以在不同情况下以较低或较高的智能运行。 MetrInt是一个精确的度量,它考虑了智能表现形式的可​​变性。即使在群体系统的智能差异很小的情况下,它也有效。可以将具有相同智能级别的两个群体系统视为同一智能类别。

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