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From the Real Ant to the Artificial Ant: Applications in Combinatorial Optimization, Data Clustering, Collective Robotics and Image Processing

机译:从真正的蚂蚁到人工蚂蚁:在组合优化,数据聚类,集体机器人和图像处理中的应用

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摘要

Biological studies highlighting the collective behavior of ants in fulfilling various tasks by using their complex indirect communication process have constituted the starting point for many physical systems and various ant colony algorithms. Each ant colony is considered as a superorganism which operates as a unified entity made up of simple agents. These agents (ants) interact locally with one another and with their environment, particularly in finding the shortest path from the nest to food sources without any centralized control dictating the behavior of individual agents. It is this coordination mechanism that has inspired researchers to develop plenty of metaheuristic algorithms in order to find good solutions for NP-hard combinatorial optimization problems. In this article, the authors give a biological description of these fascinating insects and their complex indirect communication process. From this rich source of inspiration for researchers, the authors show how, through the real ant, artificial ant is modeled and applied in combinatorial optimization, data clustering, collective robotics, and image processing.
机译:生物学研究强调了蚂蚁通过使用其复杂的间接通信过程来完成各种任务的集体行为,这已成为许多物理系统和各种蚁群算法的起点。每个蚁群都被视为一个超生物,它是由简单代理组成的统一实体。这些媒介(蚂蚁)彼此之间以及它们与周围的环境在局部相互作用,尤其是在寻找从巢到食物来源的最短路径时,没有任何集中控制来指示单个媒介的行为。正是这种协调机制激发了研究人员开发大量的元启发式算法,以便为NP-hard组合优化问题找到良好的解决方案。在本文中,作者对这些引人入胜的昆虫及其复杂的间接交流过程进行了生物学描述。从研究者的丰富灵感中,作者展示了如何通过真实的蚂蚁对人工蚂蚁进行建模,并将其应用于组合优化,数据聚类,集体机器人和图像处理。

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