Donald A. Sofge

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Using computational intelligence, our ultimate goal is to self-regulate systems composed of humans, machines and robots. Self-regulation is important for the control of mixed organizations and systems. An overview of self-regulation for organizations and systems, characterized by our solution of the tradeoffs between Fourier pairs of Gaussian distributions(More)
Game theory's popularity continues to increase in a variety of disciplines such as economics, biology, political science, computer science, electrical engineering, business, law, public policy, and many others. The focus of this symposium was to bring together the community working on applied computational game theory motivated by any of these domains. This(More)
— This paper proposes a path-planning approach to enable a team of unmanned aerial vehicles (UAVs) to efficiently conduct surveillance of sensitive areas. The proposed approach, termed PARCOV (Planner for Autonomous Risk-sensitive Coverage), seeks to maximize the area covered by the sensors mounted on each UAV while maintaining high sensor data quality and(More)
In this report we address the role of trust in autonomous systems, and our progress in developing a theory of interdependence for the efficient control of hybrid teams and systems composed of robots, machines and humans working interchangeably. Sentient multi-agent systems require an aggregation process like data fusion. But conventional use of fusion for(More)
Traditional social science research has been unable to satisfactorily aggregate individual level data to group, organization and systems levels, making it one of social science's biggest challenges (Giles, 2011). For game and social theory , we believe that the fault can be attributed to the lack of valid distance measures (e.g., the arbitrary ordering of(More)