Welfarist Control Design -- How to fulfill the societal mandate in multi-agent control?
For control engineers designing automated resource allocation systems, this work provides a principled framework to replace ad-hoc industry norms with ethically grounded design objectives.
This paper addresses the challenge of designing multi-agent control systems that align with societal preferences, proposing a welfarist approach that aggregates individual preferences into control objectives. It demonstrates that feedback control paradigms like online feedback optimization, Markov decision processes, and model predictive control can effectively allocate scarce resources in socio-technical systems.
At the core of most socio-technical systems lies a scarce resource that is allocated among agents: highway lanes, public transit, road space, water rights, energy access, grid capacity, user attention, pollution rights, etc. With further automation of the underlying allocation processes, control engineers are increasingly tasked to make decisive assumptions regarding what society wants. In practice to date, design choices are largely driven by industry norms and conventions rather than a result of conscientiously responsible and ethical design. In this paper, we look at tools available to control engineers to design systems in a more principled manner in order to match the societal mandate. We consider three control design paradigms: online feedback optimization, control of Markov decision processes, and model predictive control. Beginning with aggregating individual agents' preferences into control design objectives, subsequently ensuring and certifying the fulfillment of those specifications, we argue that the feedback nature of control systems enables appropriate allocation of the shared resources in ways hitherto unparalleled.