In this paper an agent-based simulation is developed in order to evaluate an AmI scenario based on agents. Many AmI applications are implemented through agents but they are not compared to any other existing alternative in order to evaluate the relative benefits of using them. The proposal simulation environment developed in Netlogo analyse 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. So, here, a previously suggested agent architecture, an ontology and a 12-steps protocol to provide AmI services in airports, is evaluated using a NetLogo simulation environment. The present work uses a NetLogo model considering scalability problems 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 presented simulates an airport with agent users passing through several zones located in a specific order in a map: passport controls, check-in counters of airline companies, boarding gates, different types of shopping. Although initial data in simulations are generated randomly, and the model is just an approximation of real-world airports, the definition of this case of use of Ambient Intelligence through NetLogo agents opens an interesting way to evaluate the benefits of using Ambient Intelligence, which is a significant contribution to the final development of them.

翻译：本文开发了一种基于智能体的仿真方法，以评估基于智能体的智能环境（AmI）场景。现有许多AmI应用通过智能体实现，但缺乏与现有替代方案的对比来评估其相对优势。本文提出的Netlogo仿真环境从两个评价标准分析这些优势：第一，衡量执行过程中不同类型愿望的智能体满意度；第二，衡量通过正确使用上下文信息所节省的时间。因此，本文采用Netlogo仿真环境，对先前提出的面向机场AmI服务的智能体架构、本体和12步协议进行了评估。本研究使用的Netlogo模型考虑了该应用领域的可扩展性问题，同时采用FIPA和BDI扩展以保持与先前工作及其JADE实现的一致性。该Netlogo模型模拟了一个机场场景，其中智能体用户依次经过地图上特定顺序布局的多个区域：护照检查区、航空公司值机柜台、登机口以及不同类型的商店。尽管模拟初始数据为随机生成，且模型仅为真实机场的近似表示，但通过Netlogo智能体定义这一环境智能应用案例，为评估环境智能效益开辟了新的途径，这对环境智能技术的最终发展具有重要贡献。