Comparing cooperative geometric puzzle solving in ants versus humans

认知 计算机科学 可扩展性 不相交集 集体智慧 抓住 认知心理学 人工智能 人机交互 心理学 数学 组合数学 数据库 神经科学 程序设计语言
作者
Tabea Dreyer,Amir Haluts,Amos Korman,Nir S. Gov,Ehud Fonio,Ofer Feinerman
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [Proceedings of the National Academy of Sciences]
卷期号:122 (1) 被引量:3
标识
DOI:10.1073/pnas.2414274121
摘要

Biological ensembles use collective intelligence to tackle challenges together, but suboptimal coordination can undermine the effectiveness of group cognition. Testing whether collective cognition exceeds that of the individual is often impractical since different organizational scales tend to face disjoint problems. One exception is the problem of navigating large loads through complex environments and toward a given target. People and ants stand out in their ability to efficiently perform this task not just individually but also as a group. This provides a rare opportunity to empirically compare problem-solving skills and cognitive traits across species and group sizes. Here, we challenge people and ants with the same “piano-movers” load maneuvering puzzle and show that while ants perform more efficiently in larger groups, the opposite is true for humans. We find that although individual ants cannot grasp the global nature of the puzzle, their collective motion translates into emergent cognitive skills. They encode short-term memory in their internally ordered state and this allows for enhanced group performance. People comprehend the puzzle in a way that allows them to explore a reduced search space and, on average, outperform ants. However, when communication is restricted, groups of people resort to the most obvious maneuvers to facilitate consensus. This is reminiscent of ant behavior, and negatively impacts their performance. Our results exemplify how simple minds can easily enjoy scalability while complex brains require extensive communication to cooperate efficiently.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
澎湃完成签到,获得积分10
刚刚
刚刚
专注以菱完成签到,获得积分20
刚刚
刚刚
刚刚
不安枫发布了新的文献求助10
刚刚
1秒前
1秒前
翔君发布了新的文献求助10
1秒前
翔君发布了新的文献求助10
1秒前
翔君发布了新的文献求助10
2秒前
tjr8910发布了新的文献求助10
2秒前
慕青应助yyyy采纳,获得10
3秒前
to_be_pride完成签到,获得积分10
3秒前
nlidexiaoyang完成签到,获得积分20
3秒前
iW发布了新的文献求助10
3秒前
3秒前
hbhbj发布了新的文献求助10
3秒前
zahngyacheng完成签到,获得积分10
3秒前
4秒前
Dawn发布了新的文献求助30
4秒前
大力的鱼发布了新的文献求助10
4秒前
子非鱼完成签到 ,获得积分10
5秒前
ding应助momo采纳,获得10
5秒前
5秒前
6秒前
福福气完成签到,获得积分10
6秒前
7秒前
翔君发布了新的文献求助10
7秒前
体贴成危完成签到,获得积分10
7秒前
丘比特应助周新哲采纳,获得10
7秒前
翔君发布了新的文献求助10
7秒前
8秒前
77发布了新的文献求助10
8秒前
爱听歌依波完成签到,获得积分10
9秒前
9秒前
11秒前
11秒前
爱听歌契发布了新的文献求助10
11秒前
白白白发布了新的文献求助10
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Aerospace Standards Index - 2026 ASIN2026 3000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
Research Methods for Business: A Skill Building Approach, 9th Edition 500
Social Work and Social Welfare: An Invitation(7th Edition) 410
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6048562
求助须知:如何正确求助?哪些是违规求助? 7832701
关于积分的说明 16259909
捐赠科研通 5193835
什么是DOI,文献DOI怎么找? 2779102
邀请新用户注册赠送积分活动 1762405
关于科研通互助平台的介绍 1644611