系统之系统的基于智能体建模
Agent-Based Modeling of Systems of Systems
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中文总结 AI 辅助
本文提出一种基于智能体的通用形式化方法，用于建模系统之系统的复杂性与组织、功能及多层面方面，并通过智能自主车辆案例验证其有效性。
中文摘要 AI 辅助
本文探讨了使用基于智能体的建模方法对系统之系统（SoSs）进行通用建模。系统之系统是大型系统，包含众多可能异构且相互作用的组件系统，这些系统在动态环境中演化。本文旨在提供一种通用形式化方法，使得能够通过基于智能体的仿真来表示和控制系统之系统的整体复杂性。具体而言，系统之系统的组织方面通过智能体-组-角色模型进行管理。功能方面，即引导系统之系统实现其全局目标的功能，通过功能规范来处理。多层面方面则使用用于多层面仿真的影响反应模型（IRM4MLS）这一基于智能体的元模型进行建模。使用该形式化方法生成的模型涵盖了系统之系统的静态和动态方面。它们考虑了由目标变化或子系统能力变化引起的系统之系统的重组。本文通过一个系统之系统的案例研究来阐述所有这些要素，该案例研究涉及智能自主车辆，源自欧洲项目“动态环境智能交通”（InTraDE），旨在实现港口集装箱物流的自动化。
英文摘要
This paper deals with the generic modeling of systems of systems (SoSs) using agent-based modeling. SoSs are large-scale systems, including numerous-possibly heterogeneous-interacting component systems evolving in a dynamic environment. The aim of this paper is to provide generic formalism allowing to represent and control the whole complexity of a SoS using agent-based simulations. In particular, organizational aspects of SoSs are managed with the Agent-Group-Role model. Functional aspects, guiding SoSs to accomplish their global goals, are handled via a functional specification. Multilevel aspects are modeled with the Influence Reaction Model for Multilevel Simulation (IRM4MLS) agent-based meta-model. Models generated using this formalism encompass static and dynamic aspects of SoSs. They consider reorganization of SoSs caused by changes of goals or subsystem capacity. All these elements are illustrated in this paper using a SoS case study of Intelligent Autonomous Vehicles initiated by the Intelligent Transportation for Dynamic Environment (InTraDE) European project to automate the port container logistic.
