Evolutionary dynamics of division of labor games with selfish agents

Department of Automation, College of Computer and Control Engineering, Nankai University Tianjin 300071, China and Tianjin Key Laboratory of Intelligent Robotics, Nankai University - Tianjin 300071, China

^(a) zhcy@nankai.edu.cn

Received: 24 October 2017
Accepted: 5 January 2018

Abstract

The division of labor is one of the most basic and widely studied aspects of collective behavior in natural systems. Studies of division of labor are concerned with the integration of the individual worker behavior into a colony level task organization and with the question of how the regulation of the division of labor may contribute to the colony efficiency. This paper investigates the evolution of the division of labor with three strategies by employing the evolutionary game theory. Thus, these available strategies are, respectively, strategy A (performing task A), strategy B (performing task B), and strategy D (not performing any task but only free riding others' contributions). And, two typical networks (i.e., BA scale-free network and lattice network) are employed here for describing the interaction structure among agents. The theoretical analysis together with simulation results reveal that the division of labor can evolve and leads to players that differ in their tendency to take on a given task. The conditions under which the division of labor evolves depend on the costs for performing the task, the benefits led by performing the task, and the interaction structures among the players who are involved with division of labor games.