Artificial adaptive agent model characterized by learning and fairness in the ultimatum games

Abstract

This paper examines the result of the experimental research on the ultimatum games through simulation analysis. To do so, we develop agent-based simulation system imitating the behavior of human subjects in the laboratory experiment by implementing a learning mechanism involving a concept of fairness. In our agent-based simulation system, mechanisms of decision making and learning are constructed on the basis of neural networks and genetic algorithms.