Economic Experiments with Swarm: A Neural Network Approach to the Self-Development of Consistency in Agents’ Behavior

We underline the usefulness of agent based models in the social science perspective, also focusing on the main computational problems due to the structure of our models: to simplify the task we introduce a generalized Environment-Rules-Agents scheme. Finally, within Swarm, we introduce a neural network tool (Cross Target method), useful in building artificial laboratories, for experiments with learning, self-developed consistency and interaction of agents in artificial worlds, in order to observe the emergence of complexity without a priori behavioral rules.