Abstract
Abstract : This project addresses two challenges in complex human-machine systems: i) predicting system responses that emerge from the combined actions of multiple networked agents and ii) designing components to establish desirable system operations from collective agent behaviors. In complex human machine systems, the agents are comprised of both programmable components and human decision makers. An ultimate objective is to enable effectively controlled coordination of this combination through the development of computational algorithms and human incentives supported by analysis, simulation, fielded surveys, and operational performance feedback. Work has continued on two complementary directions towards our objective. First is the analysis and simulation of agent coordination. Second is understanding the emergence of patterns and interactions among organizational cultural norms, through the use of fielded surveys and operational performance feedback, specifically in the area of organizational safety for high-risk, high-consequence systems.
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