Distribution of Control Effort in Multi-Agent Systems : Autonomous systems of the world, unite!

Abstract: As more industrial processes, transportation and appliances have been automated or equipped with some level of artificial intelligence, the number and scale of interconnected systems has grown in the recent past. This is a development which can be expected to continue and therefore the research in performance of interconnected systems and networks is growing. Due to increased automation and sheer scale of networks, dynamically scaling networks is an increasing field and research into scalable performance measures is advancing. Recently, the notion gamma-robustness, a scalable network performance measure, was introduced as a measurement of interconnected systems robustness with respect to external disturbances. This thesis aims to investigate how the distribution of control effort and cost, within interconnected system, affects network performance, measured with gamma-robustness. Further, we introduce a notion of fairness and a measurement of unfairness in order to quantify the distribution of network properties and performance. With these in place, we also present distributed algorithms with which the distribution of control effort can be controlled in order to achieve a desired network performance. We close with some examples to show the strengths and weaknesses of the presented algorithms.