Division of Labor as the Result of Phase Transition

TL;DR

This paper models the emergence of labor division in multi-agent systems as a phase transition using statistical physics, revealing how technical progress and cooperation influence this phenomenon.

Contribution

It introduces a novel statistical physics-based model that explains labor division as a phase transition influenced by technical progress and cooperation.

Findings

Labor division emerges as a phase transition at a critical point.

Technical progress determines the occurrence of phase transition.

Competitive cooperation significantly affects the critical point.

Abstract

The emergence of labor division in multi-agent system is analyzed by the method of statistical physics. Considering a system consists of N homogeneous agents. Their behaviors are determined by the returns from their production. Using the Metropolis method in statistical physics, which in this model can been regarded as a kind of uncertainty in decision making, we constructed a Master equation model to describe the evolution of the agents distribution. When we introduce the mechanism of learning by doing to describe the effect of technical progress and a formula for the competitive cooperation, the model gives us the following interesting results: (1) As the results of long term evolution, the system can reach a steady state. (2) When the parameters exceed a critical point, the labor division emerges as the result of phase transition. (3) Although the technical progress decides whether or not phase transition occurs, the critical point is strongly effected by the competitive cooperation. From the above physical model and the corresponding results, we can get a more deeply understanding about the labor division.