Metabolism of Social System

TL;DR

This paper models social system metabolism using a Boolean network approach to analyze cooperation and defection dynamics in multi-agent games, revealing how system size and input complexity affect stability and equilibrium.

Contribution

It introduces a novel application of Boolean networks to simulate social interactions and cooperation strategies in multi-agent systems, highlighting effects of input complexity on system stability.

Findings

Systems with fewer inputs reach equilibrium faster.

Larger systems stabilize over strategies more slowly.

Stable equilibrium is achieved despite longer convergence times.

Abstract

Random Boolean Network has been used to find out regulation patterns of genes in organism. his approach is very interesting to use in a game such as N Person PD. Here we assume that action is influenced by input in the form of choices of cooperate or defect he accepted from other agent or group of agents in the system. Number of cooperators, pay off value received by each agent, and average value of the group pay off, are observed in every state, from initial state chosen until it reaches its state cycle attractor. In simulation performed here, we gain information that a system with large number agents based on action on input K equals to two, will reach equilibrium and stable condition over strategies taken out by its agents faster than higher input, that is K equals to three. Equilibrium reached in longer interval, yet it is stable over strategies carried out by agents.