在集体食中使用视觉社会信息
David Mezey1,2, Dominik Deffner2,3, Ralf H J M Kurvers2,3
1Institute for Theoretical Biology, Humboldt University Berlin, Berlin, Germany.
PLoS computational biology
|May 3, 2024
概括
了解个人决策如何导致群体行为是关键. 这项研究模拟了集体食,展示了环境和约束因素塑造了信息的使用,以获得最佳的群体结果.
科学领域:
- 生态生态学 生态生态学
- 行为生态学 行为生态学
- 计算生物学 计算生物学
背景情况:
- 集体动态源于个人的决定,但与现实世界结果的联系尚不清楚.
- 了解信息使用 (个人与社会) 对集体行为至关重要.
- 基于代理的模型提供了一种探索这些复杂相互作用的方法.
研究的目的:
- 机械地将个人决策与集体食结果联系起来.
- 调查使用个人信息和社会信息之间的权衡.
- 探索环境和物理约束对集体绩效的影响.
主要方法:
- 开发了一个空间显式的,基于代理的模型,模拟个人证据的积累.
- 集成的个人 (内部) 和社会 (视觉) 线索与基于粒子的运动.
- 在理想化和受约束环境中模拟集体食.
主要成果:
- 该模型在理想化的条件下重现了已确定的发现,解释了自下而上的出现.
- 最佳的集体表现取决于环境结构:在统一的环境中,在集群,个人主义的搜索中,强大的社会影响.
- 身体和感知上的限制显著改变了集体动态,有时可以防止不适应的群体.
结论:
- 揭示了连接个人认知与人类和动物集体食的机制.
- 展示环境背景和约束如何调节信息使用策略.
- 为设计集体任务的分散式机器人系统提供了一个框架.
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