The aim of this work is to construct a microscopic model of multi-agent interaction networks inspired by foraging ants that do not use pheromone trails or stigmergic traces for communications. The heading and speed of each agent is influenced by direct interactions or encounters with other agents. Each agent moves in a plane using a correlated random walk whose probability distribution for heading change is made adaptable to these interactions and is superimposed with probability distributions that emulate how ants remember nest and food source locations. The speed of each agent is likewise influenced by a superposition of impetus and resistance effects that arise from its recent interactions. Additionally, the agents use a quorum sensing mechanism to trigger a non-deterministic decentralized congestion avoidance scheme. A discrete-time non-deterministic recruitment model is adopted and incorporated to regulate the population of foraging agents based on the amount of food perceived to exist in the environment. Simulation experiments were conducted to evaluate and demonstrate how agents employ the interaction network when foraging in open and closed environments as well as in scenarios with narrow pathways that trigger congestion.

中文翻译：

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无需Stigmergy的多主体交互网络的蚂蚁启发模型

这项工作的目的是构建一个多主体交互网络的微观模型，该模型受觅食蚂蚁的启发，这些蚂蚁不使用信息素踪迹或光辉痕迹进行通讯。每个代理的前进方向和速度受与其他代理的直接交互或相遇的影响。每个特工使用相关的随机游走在平面上移动，其航向改变的概率分布使其适应于这些交互作用，并与模拟蚂蚁记住巢穴和食物来源位置的概率分布叠加。每种作用剂的速度同样受其最近相互作用产生的动力和阻力作用叠加的影响。另外，代理使用仲裁感测机制来触发非确定性分散拥塞避免方案。采用了离散时间的不确定性招聘模型，该模型根据已知存在于环境中的食物量来调节觅食剂的数量。进行了模拟实验，以评估和演示代理在开放和封闭环境中以及在狭窄路径引发拥塞的场景中觅食时如何利用交互网络。