CAREER: Understanding Strategic Dynamics in the Engineering of Decentralized Systems

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This Faculty Early Career Development Program (CAREER) grant will diagnose and provide understanding of strategic dynamics among a set of interactive and autonomous design actors through the combined use of game theory and simulations to inform architecture and design decisions. Design activities for engineering systems across infrastructure, aerospace, and defense domains more closely resemble a collective decision-making process than centralized authority in traditional systems engineering practice. This topic is of interest because U.S. agencies and firms are actively architecting systems with decentralized decision authority, described variously as Internet 4.0, cyber-physical systems, Internet-of-things, or systems-of-systems across domains, including energy, transportation, manufacturing, and space systems. The design of these engineering systems differs from that of other systems because their large scale, long lifetime, and proximity to social systems evoke complex features such as adaptation, self-organization, and emergence, which take place over strategic timescales. A deeper understanding of how strategic dynamics impact designer interactions across theoretical and empirical perspectives can help to avoid costly overruns and cancellations by identifying and mitigating undesirable dynamics in conceptual design phases. Advances in systems engineering must develop theory, methods, and tools to coordinate and facilitate collective design activities. This project builds on a line of economic methods applied to engineering design including utility theory, decision theory, social choice, and game theory. Collective systems design is modeled as a bi-level problem, where lower-level decisions correspond to an optimization problem and upper-level strategy decisions correspond to a coordination game. Normative models of agent behavior are based on classical and Bayesian game theory with utility functions incorporating behavioral factors such as risk attitudes. Multi-agent simulation studies evolution of strategies under repeated interaction among agents. Behavioral experiments collect empirical data about human decision-making for validation. The research will contribute new knowledge about how to characterize, study, and modify the strategic dynamics of engineering systems during conceptual design phases. The educational plan develops and delivers simulation activities to model systems problems by combining technical modeling and social interaction. The simulation activities behave as a highly abstracted model system to elicit rich strategic behaviors through face-to-face interaction, engage students with challenges of socio-technical problems, and retain computational tractability to teach analytical methods in educational contexts. Development and broad public dissemination of simulations in the context of Earth science space missions will expose a wide audience to strategic issues of government-commercial interdependency in space systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.