Agent-based simulation with NetLogo to evaluate ambient intelligence scenarios

In this paper, an agent-based simulation is developed in order to evaluate an Ambient Intelligence scenario based on agents. Many AmI applications are implemented through agents but they are not compared with any other existing alternative in order to evaluate the relative benefits of using them. The proposed simulation environment analyses such benefits using two evaluation criteria: First, measuring agent satisfaction of different types of desires along the execution. Second, measuring time savings obtained through a correct use of context information. In this paper, an existing agent architecture, an ontology and a 12-steps protocol to provide AmI services in airports, is evaluated using the NetLogo simulation environment. In our NetLogo model, we are considering scalability issues of this application domain but using FIPA and BDI extensions to be coherent with our previous works and our previous JADE implementation of them. The NetLogo model simulates an airport with agent “passengers” passing through several zones located in a specific order in a map: passport controls, check-in counters of airline companies, boarding gates, and different types of shopping. Although the initial data in each simulation are generated randomly, and the model is just an approximation of real-world airports, the definition of this case of use of AmI through NetLogo agents opens an interesting way to evaluate the benefits of using AmI, which is a significant contribution to the final development of AmI systems.