Plasczyk Tobias, Monderkamp Paul A, Löwen Hartmut, Wittmann René
Institut für Theoretische Physik II: Weiche Materie, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225, Düsseldorf, Germany.
Institut für Sicherheit und Qualität bei Fleisch, Max Rubner-Institut, E.-C.-Baumann-Straße 20, 95326, Kulmbach, Germany.
Eur Phys J E Soft Matter. 2025 Jan 3;48(1):1. doi: 10.1140/epje/s10189-024-00465-0.
Intelligent decisions in response to external informative input can allow organisms to achieve their biological goals while spending very little of their own resources. In this paper, we develop and study a minimal model for a navigational task, performed by an otherwise completely motorless particle that possesses the ability of hitchhiking in a bath of active Brownian particles (ABPs). Hitchhiking refers to identifying and attaching to suitable surrounding bath particles. Using a reinforcement learning algorithm, such an agent, which we refer to as intelligent hitchhiking particle (IHP), is enabled to persistently navigate in the desired direction. This relatively simple IHP can also anticipate and react to characteristic motion patterns of their hosts, which we exemplify for a bath of chiral ABPs (cABPs). To demonstrate that the persistent motion of the IHP will outperform that of the bath particles in view of long-time ballistic motion, we calculate the mean-squared displacement and discuss its dependence on the density and persistence time of the bath ABPs by means of an analytic model.
对外部信息输入做出的明智决策能够使生物体在消耗极少自身资源的情况下实现其生物学目标。在本文中，我们开发并研究了一个用于导航任务的极简模型，该任务由一个原本完全无动力的粒子执行，该粒子具有在活性布朗粒子（ABP）浴中搭便车的能力。搭便车是指识别并附着在合适的周围浴粒子上。使用强化学习算法，这样一个我们称为智能搭便车粒子（IHP）的智能体能够在期望的方向上持续导航。这个相对简单的IHP还能够预测并对其宿主的特征运动模式做出反应，我们以手性ABP（cABP）浴为例进行说明。为了证明从长时间弹道运动的角度来看IHP的持续运动会优于浴粒子的运动，我们计算均方位移，并通过一个解析模型讨论其对浴ABP的密度和持续时间的依赖性。
