Agent-based simulation analysis for social norms

With existence of the social custom or norm, Naylor demonstrates a possibility of stable long-run equilibria of support for a strike in a labor market, and this implies that at least some individuals will behave cooperatively and hence the prisoners´ dilemma could be escaped. In this paper, we develop an agent-based simulation system in which artificial adaptive agents have mechanisms of decision making and learning based on neural networks and genetic algorithms, and compare the result of our simulation analysis with that of the mathematical model by Naylor. Especially, while the Naylor model is based on rationality about maximization of individual utility, our agent-based simulation model employs adaptive behavior of agents; agents make decisions by trials and errors and they learn from experiences to make better decisions.