Social search has stably evolved across various species and is often used by humans to search for resources (such as food, information, social partners). In turn, these resources frequently come distributed in patches or clusters. In the current work, we use an ecologically inspired agent-based model to investigate whether social search and clustering are stable outcomes of the dynamical mutual interactions between the two. While previous research has studied unidirectional influences of social search on resource clustering and vice versa, the current work investigates the consequential patterns emerging from their two-way interactions over time. In our model, consumers evolved search strategies (ranging from competitive to social) as adaptations to their environmental resource structures, and resources varied in distributions (ranging from random to clustered) that were shaped by agents’ consumption patterns. Across four experiments, we systematically analyzed the patterns of influence that search strategies and environment structure have on each other to identify stable attractor states of both. In Experiment 1, we fixed resource clustering at various levels and observed its influence on social search, and in Experiment 2, we observed the influence of social search on resource distribution. In both these experiments we found that increasing levels of one variable produced increases in the other; however, at very high levels of the manipulated variable, the dependent variable tended to fall. Finally in Experiments 3 and 4, we studied the dynamics that arose when resource clustering and social search could both change and mutually influence each other, finding that low levels of social search and clustering were stable attractor states. Our simple 2D model yielded results that qualitatively resemble those across a wide range of search domains (from physical search for food to abstract search for information), highlighting some stable outcomes of mutually interacting consumer/resource systems.

社交搜索已经在各种物种中稳定发展，并且经常被人类用来搜索资源（例如食物、信息、社交伙伴）。反过来，这些资源经常以补丁或集群的形式分布。在目前的工作中，我们使用受生态启发的基于代理的模型来研究社交搜索和聚类是否是两者之间动态相互作用的稳定结果。虽然之前的研究研究了社交搜索对资源集群的单向影响，反之亦然，但当前的工作调查了随着时间的推移从它们的双向交互中出现的相应模式。在我们的模型中，消费者进化了搜索策略（从竞争到社交）以适应他们的环境资源结构，资源的分布（从随机到集群）各不相同，这些分布由代理人的消费模式决定。在四个实验中，我们系统地分析了搜索策略和环境结构相互影响的模式，以确定两者的稳定吸引子状态。在实验一中，我们将资源聚类固定在不同层次，观察其对社交搜索的影响，在实验二中，我们观察社交搜索对资源分配的影响。在这两个实验中，我们发现一个变量水平的增加会导致另一个变量的增加；然而，在非常高的操纵变量水平下，因变量往往会下降。最后在实验 3 和 4 中，我们研究了当资源​​集群和社交搜索可以同时改变并相互影响时出现的动态，发现低水平的社交搜索和集群是稳定的吸引子状态。我们简单的 2D 模型产生的结果在质量上类似于广泛的搜索领域（从物理搜索食物到抽象信息搜索），突出了消费者/资源系统相互作用的一些稳定结果。