Article ; Online: Complexity synchronization in emergent intelligence.
2024 Volume 14, Issue 1, Page(s) 6758
Abstract: 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 ... ...
Abstract | 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. |
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MeSH term(s) | Humans ; Algorithms ; Intelligence ; Entropy |
Language | English |
Publishing date | 2024-03-21 |
Publishing country | England |
Document type | Journal Article |
ZDB-ID | 2615211-3 |
ISSN | 2045-2322 ; 2045-2322 |
ISSN (online) | 2045-2322 |
ISSN | 2045-2322 |
DOI | 10.1038/s41598-024-57384-5 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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