Preliminary Evolutionary Network Model for Efficient Collaboration in Systems-of-Systems

Abstract

Collaborative systems-of-systems (CSoSs) are defined by the Systems Engineering Body of Knowledge as groups of constituent systems that voluntarily work with each other toward a common goal. As the complexity, sociotechnical interactions, and cooperation of real systems increases, so too does our need to understand how to design and manage collaboration across disciplines. An agent-based model is developed that combines network evolution mechanisms with evolutionary game theory to simulate CSoSs. Collaboration efficiency (CE) is introduced as a metric by which collaboration may be measured and performance compared. Cost and strategy parameters of constituent systems are tested via CSoS model simulation to develop insights into best collaboration practices for CSoSs. Results suggest a reactive collaboration strategy or a reinforcement algorithm-based strategy produce the highest CE under certain conditions. Applicable to systems in sociotechnical enterprises, logistics, energy, infrastructure, and more, this research can improve the design and operation of any CSoS.