System of systems (SoS) concept is essential in solving the issues in complex systems where there are heterogeneous independently operable systems. In order for these independent systems to establish an SoS, they need to understand each other through effective communication. Thus, there is a need for a common language which wraps the data that is sent and received from a system within an SoS. This paper presents the application of extensible markup language (XML) to represent data communicated among systems without underlying differences in hardware software of the individual systems. Moreover, since the operation of each system is asynchronous in nature, the entire SoS can be considered as an event driven system. This paper presents a simulation framework to simulate the structure of the systems in an event driven fashion and wraps the data with a common language. The DEVSJAVA software is used as the discrete event simulator. In addition, XML based encapsulation is created in the DEVSJAVA environment to in the SoS.

This paper presents machine learning concepts to successfully implement an intelligent agent solution to the problem of autonomous control of Personal Rapid Transit (PRT) vehicles. The PRTs can operate independently and together as a whole system. Thus, they can be considered as a system of systems. By developing a set of rules for the vehicles to follow, the various parts of a Bayesian Network (BN), its nodes, parameters, structure and utility function are determined. The variables in the network are generated from the sensor data of the PRT vehicles. Using the overall system goals, a utility function can be devised that will select the best action for an agent to take. Simulation results show that this methodology is useful for "rapid prototyping" a decision theoretic agent. The gap between the intelligent agent and rule based agent performance for the collision metrics suggests that more research is needed to develop a systematic method of creating utility functions to meet system goals.