.png){kind=icon}
返回
Complexity synchronization in emergent intelligence
.png){kind=icon}
OA
AI
DOI：10.1038/s41598-024-57384-5.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this work, we use a simple multi-agent-based-model (MABM) of a social network, implementing selfish algorithm (SA) agents, to create an adaptive environment and show, using a modified diffusion entropy analysis (DEA), that the mutual-adaptive interaction between the parts of such a network manifests complexity synchronization (CS). CS has been shown to exist by processing simultaneously measured time series from among organ-networks (ONs) of the brain (neurophysiology), lungs (respiration), and heart (cardiovascular reactivity) and to be explained theoretically as a synchronization of the multifractal dimension (MFD) scaling parameters characterizing each time series. Herein, we find the same kind of CS in the emergent intelligence of groups formed in a self-organized social interaction without macroscopic control but with biased self-interest between two groups of agents playing an anti-coordination game. This computational result strongly suggests the existence of the same CS in real-world social phenomena and in human-machine interactions as that found empirically in ONs.
Keyword:
Complexity synchronization
Modified diffusion entropy analysis
Emergent intelligence
Adaptive environment
Multi-agent-based-modeling
Selfish algorithm
Reinforcement learning
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.9
论文数:
28.3W
被引数:
83.5W
机构
引用论文
分享收藏分享收藏Critical dynamics of endogenous fluctuations predict cognitive flexibility in the Go/NoGo task.png)
SCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏Complexity synchronization: a measure of interaction between the brain, heart and lungsSCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏
查看更多内容