Agent-based Models Predicting Collective Behaviors

We present a Virtual Ant Laboratory agent-based model, an interactive and prediction tool to simulate the ants' environment and their decisions making and foraging behaviors. The proposed simulation model provides the ability to generate customized complex ant environments and to explore the interaction between the environment features and ants' behavior. As expected, the results showed that the quality of the food and the distance between food sources and the nest have a significant impact on the ants' decisions. The model was partially validated via live-ants laboratory experiments and can easily be generalized to other environments/agents.