| 郭晓辉,2025,蚁群的秘密：群体行为背后的“精算”[J].环境昆虫学报,(1):117-127 |
| 蚁群的秘密：群体行为背后的“精算” |
| Secrets of ant colonies: “Computations” behind their collective behaviors |
| |
| DOI： |
| 中文关键词: 蚁群 自组织过程 群体行为 社会分工 群体感应 协同搬运 |
| 英文关键词:Ant colonies self-organized process collective behavior division of labor quorum sensing cooperative transport |
| 基金项目: |
|
| 摘要点击次数: 3 |
| 全文下载次数: 3 |
| 中文摘要: |
| 本综述探讨了蚂蚁的群体行为，以理解去中心化、自组织系统如何实现复杂的协调性、适应性和稳定性，进而促使蚂蚁成为全球最成功、分布最广泛的物种之一。蚂蚁成功背后的三大关键群体行为特征，共同提升了蚁群的整体效能：（1）个体异质性，不同个体具备多样化的特质，支持在蚁群内扮演不同的专门化角色；（2）基于任务的个体合作，使蚂蚁能够完成单个个体无法独立实现的目标；（3）分布式决策与信息流动，优化了蚁群在变化环境下的响应能力和弹性。通过经典案例如任务分配、协同搬运和基于最小有效多数的决策机制，展示了这些特征如何帮助蚂蚁灵活适应其环境，同时强调了数学建模作为研究框架的作用，通过定量分析为理解这些复杂行为提供了精准的见解。对蚁群行为的量化和建模对于将自然智慧转化为可扩展、适应性强的人类社会问题解决方案具有重要意义。 |
| 英文摘要: |
| This review explores the collective behaviors of ant colonies to understand how decentralized, self-organized systems achieve complex coordination, adaptability, and stability, which makes ant one of the most successful and widespread species globally. It highlights three key features of collective behavior behind the success of ant species that contribute to colony effectiveness: (1) individual heterogeneity, where varied traits support specialized roles within the colony; (2) task-oriented cooperation among individuals, allowing them to accomplish objectives beyond individual capacity; and (3) distributed decision-making and information flow, which optimize responses and resilience under changing conditions. Classic examples, including task allocation, cooperative transport, and quorum-based decision-making, illustrate how these three features enable ants to adapt flexibly to their environments. This review emphasizes the effect of mathematical modeling as a research framework, providing precise insights for these complex behaviors by quantitative analysis. Quantifying and modeling ant colony behaviors is of great significance for translating natural intelligence into scalable, adaptable solutions to human social problems. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| 关闭 |
|
|
|
