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arXiv · 2311.11407

Complexity Synchronization in Emergent Intelligence

Korosh Mahmoodi1·Scott E. Kerick·Piotr J. Franaszczuk1·Thomas D. Parsons·Paolo Grigolini·Bruce J. West
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Abstract

In this work, we use a simple multi-agent-based model (MABM), implementing selfish algorithm (SA) agents, to create an adaptive environment and show, using modified diffusion entropy analysis (MDEA), that the mutual-adaptive interaction between the parts of such a network manifests complexity synchronization (CS). CS has been experimentally shown to exist 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 scaling parameters characterizing each time series. Herein, we find the same kind of CS in the emergent intelligence (i.e., without macroscopic control and based on self-interest) between two groups of agents playing an anti-coordination game, thereby suggesting the potential for the same CS in real-world social phenomena and in human-machine interactions.

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Korosh Mahmoodi1, Scott E. Kerick, Piotr J. Franaszczuk1, Thomas D. Parsons, Paolo Grigolini, Bruce J. West. 2023-11-19. Complexity Synchronization in Emergent Intelligence. https://arxiv.org/abs/2311.11407

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