Search for: [Description = "In this paper, we give a general framework of agent\-based simulation for analyzing behavior of players in various types of games. In our simulation model, artificial adaptive agents have a mechanism of decision making and learning based on neural networks and genetic algorithms. The synaptic weights and thresholds characterizing the neural network of an artificial agent are revised in order that the artificial agent obtains larger payoffs through a genetic algorithm. The proposed framework is illustrated with two examples, and, by giving some simulation result, we demonstrate availability of the simulation analysis by the proposed framework of agent\-based simulation, from which a wide variety of simulation settings can be easily implemented and detailed data and statistics are obtained."]
