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A comparative study of swarm foraging behaviors; trophallaxis, task allocation and pheromone

机译:群体觅食行为的比较研究;横轴,任务分配和信息素

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摘要

A group of algorithm enhancing such collective behavior is inspired by the animals working together as a group such as ants, bees, and etc. In connection, swarm is defined as a set of two or more independent homogenous or heterogeneous agents acting upon a common environment in a coherent fashion which generates emergent behavior. The development of artificial swarms or robotic swarms has attracted a lot of researchers in the last two decades including pheromone, trophallaxis and task allocation algorithms. However among these swarm based algorithms, the most efficient in terms of group performance, efficiency and interference in collecting the dusts or objects in an environment with variable terrains. With this, the researchers see the need to develop a swarm simulation platform that would compare the swarm- behavior-based algorithms for an ideal use of robots in different environments in dust collection.
机译:一群增强这种集体行为的算法的灵感来自于像蚂蚁,蜜蜂等这样的动物一起工作。群体被定义为在共同的环境中起作用的两个或多个独立的同质或异质代理的集合。以连贯的方式产生突发行为。在过去的二十年中,人工蜂群或机器人蜂群的发展吸引了许多研究人员,包括信息素,对转轴和任务分配算法。但是,在这些基于群体的算法中,在具有可变地形的环境中,在收集团队中的粉尘或物体方面,团队表现,效率和干扰方面效率最高。因此,研究人员认为有必要开发一种群体模拟平台,该平台将比较基于群体行为的算法,以便在不同环境中理想地利用机器人进行集尘。

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