Agent-Based Simulation and Ontology Integration for System-of-System Exploration

The increasing interest in System-of-Systems (SoS) for engineering applications are introducing new challenges that must be overcome at an early design stage. One of these is the integration of different tools that can be used to make predictions about a system under development and how these together can be used to predict SoS performances by comparison of parameter spaces. The purpose of this paper is therefore to illustrate how different SoS architectures can be modeled, simulated, and evaluated throughout different scenarios by different teams of researchers following a common workflow. An ontology is used as an overarching knowledge base where information about entities, such as scenario details, can be extracted and used for the setup of Agent-based Simulations (ABS) through a tool integration software acting as master that controls the correct execution of the defined workflow. The tool integration software also enables additional modelling capabilities, such as a Design of Experiments (DOE) definition for design space explorations, an Optimizer with different algorithms, user-defined Python scripts, etc.