Department of Computer Science, University of Leipzig, PF 100920, D-04009 Leipzig, Germany.
J Theor Biol. 2012 Aug 7;306:32-45. doi: 10.1016/j.jtbi.2012.04.003. Epub 2012 Apr 10.
Ants live in dynamically changing environments, where food sources become depleted and alternative sources appear. Yet most mathematical models of ant foraging assume that the ants' foraging environment is static. Here we describe a mathematical model of ant foraging in a dynamic environment. Our model attempts to explain recent empirical data on dynamic foraging in the Argentine ant Linepithema humile (Mayr). The ants are able to find the shortest path in a Towers of Hanoi maze, a complex network containing 32,768 alternative paths, even when the maze is altered dynamically. We modify existing models developed to explain ant foraging in static environments, to elucidate what possible mechanisms allow the ants to quickly adapt to changes in their foraging environment. Our results suggest that navigation of individual ants based on a combination of one pheromone deposited during foraging and directional information enables the ants to adapt their foraging trails and recreates the experimental results.
蚂蚁生活在动态变化的环境中，食物源会枯竭，而其他来源会出现。然而，大多数蚂蚁觅食的数学模型假设蚂蚁的觅食环境是静态的。在这里，我们描述了一个在动态环境中蚂蚁觅食的数学模型。我们的模型试图解释最近关于阿根廷蚂蚁（Linepithema humile）动态觅食的经验数据。蚂蚁能够在汉诺塔迷宫中找到最短路径，汉诺塔迷宫是一个包含 32768 条替代路径的复杂网络，即使迷宫是动态改变的。我们修改了现有的模型来解释在静态环境中蚂蚁的觅食行为，以阐明可能的机制是什么使蚂蚁能够快速适应其觅食环境的变化。我们的结果表明，基于觅食过程中沉积的一种信息素和方向信息的个体蚂蚁导航使蚂蚁能够适应它们的觅食路径，并重现了实验结果。
