Quorum Sensing Digital Simulations for the Emergence of Scalable and Cooperative Artificial Networks

Nedjma Djezzar, Iñaki Fernández Pérez, Noureddine Djedi, Y. Duthen
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Abstract

This article proposes digital simulations of a bacterial communication system termed quorum sensing, and investigates the design of artificial networks build on the behavior of bacteria societies that tweet using quorum sensing signals. To this end, this article proposes a cell-based model that uses a “bottom-up” agent-based model coupled with ordinary differential equations, and develops the abstraction of intracellular dynamics as a basis underlying cooperative artificial network formation. Results show the emergence of self-sustainable behaviors thanks to the proposed model of metabolism that permits bacteria to grow, reproduce, interact, and coordinate at the population level to exhibit near-perfect bioluminescence behaviors. Moreover, the evolution of cooperation in the subsequent artificial network leads to the emergence of non-predicted coercive strategies. Coercion has been shown to be beneficial to share common interests between variants of cooperators leading the entire population of cells to be networked.
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群体感应数字模拟可扩展和协作人工网络的出现
本文提出了一种称为群体感应的细菌通信系统的数字模拟,并研究了基于使用群体感应信号的细菌社会行为的人工网络设计。为此,本文提出了一种基于细胞的模型,该模型使用“自下而上”的基于智能体的模型与常微分方程相结合,并将细胞内动力学的抽象作为协作人工网络形成的基础。结果表明,由于所提出的代谢模型允许细菌生长、繁殖、相互作用和在群体水平上协调以表现出近乎完美的生物发光行为,自我可持续行为的出现。此外,在随后的人工网络中,合作的进化导致了不可预测的强制策略的出现。强制已被证明有利于在不同的合作者之间分享共同利益,从而使整个细胞群体联网。
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