Scientific design of complex multi‐agent systems: A practice modeling approach

Through advances in computing power, sensor systems, networking, and AI programming, new automated systems are being developed with capabilities for acting in the world that heretofore only people could do—driving automobiles, controlling aircraft systems, delivering packages. As we give computer programs control of complicated vehicles and devices, we need new tools to create and analyze designs systemically, to anticipate and understand how people and machines will behave and interact in safety‐critical situations—when action may be urgent and lives at stake. To secure the trust of consumers and certification by regulators, engineers need to adopt scientific design methods to verify that the behavior of instruments, devices, and programs fits how people perceive, reason, and act in challenging situations.