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Geometric foraging strategies in multi-agent systems based on biological models

机译:基于生物模型的多智能体系统中的几何觅食策略

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In nature, communal hunting is often performed by predators by charging through an aggregation of prey. However, it has been noticed that variations exist in the geometric shape of the charging front; in addition, distinct differences arise between the shapes depending on the particulars of the feeding strategy. For example, each member of a dolphin foraging group must contribute to the hunt and will only be able to eat what it catches. On the other hand, some lions earn a “free lunch” by feigning help and later feasting on the prey caught by the more skilled hunters in the foraging group. We model the charging front of the predators as a curve moving through a prey density modeled as a reaction-diffusion process and we optimize the shape of the charging front in both the free lunch and no-free-lunch cases. These different situations are simulated under a number of varied types of predator-prey interaction models, and connections are made to multi-agent robot systems.
机译:在自然界中,捕食者通常通过聚集猎物来进行集体狩猎。然而,已经注意到,充电前沿的几何形状中存在变化。另外,取决于进料策略的细节,形状之间会出现明显的差异。例如,海豚觅食组的每个成员都必须为狩猎做贡献,并且只能吃掉所捕获的东西。另一方面,一些狮子通过装扮帮助并随后品尝觅食组中技术娴熟的猎人捕获的猎物而获得“免费午餐”。我们将捕食者的充电前沿建模为一条曲线,该曲线移动通过模拟为反应扩散过程的猎物密度,并且在免费午餐和非免费午餐情况下优化充电前沿的形状。在许多不同类型的捕食者与猎物交互模型下模拟了这些不同的情况,并建立了与多智能体机器人系统的连接。

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