当前位置: X-MOL 学术Front. Ecol. Evolut. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Exploring the evolution of perception: An agent-based approach
Frontiers in Ecology and Evolution ( IF 2.4 ) Pub Date : 2021-06-23 , DOI: 10.3389/fevo.2021.698041
Anshuman Swain , Tyler Hoffman , Kirtus Leyba , William F. Fagan

Perception is central to the survival of an individual for many reasons, especially as it affects the ability to gather resources. Consequently, costs associated with perception are partially shaped by resource availability. Understanding the interplay of environmental factors (such as the density and distribution of resources) with species-specific factors (such as growth rate, mutation, and metabolic costs) allows the exploration of possible trajectories by which perception may evolve. Here, we used an agent-based foraging model with a context-dependent movement strategy in which each agent switches between undirected and directed movement based on its perception of resources. This switching behavior is central to our goal of exploring how environmental and species-specific factors determine the evolution and maintenance of perception in an ecological system. We observed a nonlinear response in the evolved perceptual ranges as a function of parameters in our model. Overall, we identified two groups of parameters, one of which promotes evolution of perception and another group that restricts it. We found that resource density, basal energy cost, perceptual cost and mutation rate were the best predictors of the resultant perceptual range distribution, but detailed exploration indicated that individual parameters affect different parts of the distribution in different ways.

中文翻译:

探索感知的演变:一种基于代理的方法

出于多种原因,感知对于个人的生存至关重要,尤其是因为它会影响收集资源的能力。因此,与感知相关的成本部分取决于资源可用性。了解环境因素(例如资源的密度和分布)与物种特定因素(例如增长率、突变和代谢成本)之间的相互作用,可以探索感知可能演变的可能轨迹。在这里,我们使用了基于代理的觅食模型和上下文相关的运动策略,其中每个代理根据其对资源的感知在无向和有向运动之间切换。这种转换行为是我们探索环境和物种特定因素如何决定生态系统中感知的进化和维持的目标的核心。我们观察到作为模型参数函数的进化感知范围的非线性响应。总的来说,我们确定了两组参数,一组促进感知的进化,另一组限制它。我们发现资源密度、基础能量成本、感知成本和突变率是最终感知范围分布的最佳预测因子,但详细探索表明,各个参数以不同方式影响分布的不同部分。我们确定了两组参数,一组促进感知的进化,另一组限制它。我们发现资源密度、基础能量成本、感知成本和突变率是最终感知范围分布的最佳预测因子,但详细探索表明,各个参数以不同方式影响分布的不同部分。我们确定了两组参数,一组促进感知的进化,另一组限制它。我们发现资源密度、基础能量成本、感知成本和突变率是最终感知范围分布的最佳预测因子,但详细探索表明,各个参数以不同方式影响分布的不同部分。
更新日期:2021-06-23
down
wechat
bug