An Agent-Based Environment for Simulation Model Composition

As Modelling and Simulation gains more popularity, the demand on reducing time and resource costs associated with development and validation of simulation models has also increased. Composing simulation models of reusable and validated simulation components is one approach for addressing the above demand. This approach requires a composition process that is able to support a modeller with discovery and identification of components as well as giving feedback on feasibility of a composition. Software agents are programs that can with some degree of autonomy perform tasks on behalf of a user or another program. In a Multi Agent System (MAS) autonomous agents interact and collaborate with each other in order to solve complex problems that are beyond the individual capabilities or knowledge of each agent, thus providing modularity and scalability. The objective of this work has been to develop a Multi Agent System for discovery and composition of BOM (Base Object Model) based simulation models, which provides the flexibility and adaptability to test and assess, amongst others different discovery and composition methods and techniques. The MAS that we developed is based on the JACK^TM Intelligent Agents and executes a rule-based process for discovery and composition of BOMs. Our preliminary results indicate its feasibility, portability, adaptability and flexibility.