Designing Complex Engineering Systems using Multi-Agent Coordination Approaches

Oregon State University, Corvallis OR

Investigators

Abstract

The design of a growing class of complex systems, such as state-of-the-art aircraft, advanced power systems, unmanned aerial vehicles, and autonomous automobiles, requires the knowledge of many experts. But though each expert may be able to design a particular subsystem efficiently, the combination of those "optimal" subsystems does not generally lead to a "good" system-level design. This is because the interactions among these subsystems are critical to the performance of the complex system, and capturing the interactions becomes increasingly difficult as the systems become more and more complex. The long-term goal of this project is to address this design-decomposition problem by deriving designer-subsystem objective functions in such a way that, when all subsystem designers achieve their objectives, the overall design goals are also achieved. Traditionally, two broadly different approaches are used to design complex engineered systems: (i) a centralized design approach where the impacts of all potential system states and behaviors resulting from design decisions must be accurately modeled. (ii) a mediated design approach where externally imposed intermediate design targets are provided to determine the tradeoffs among competing designs. The mediated approach avoids the modeling difficulties of the centralized approach, but at the cost of expensive (in time and money) mediation mechanisms. The project's approach is a hybrid of the two approaches, providing a method in which decisions can be reconciled without the need for either detailed interaction models or arbitrary design targets. A key insight on which this project will build is that complex systems design is fundamentally similar to the multiagent coordination problem, that lies at the intersection of game theory, machine learning, and control theory. In both instances, the decisions at the lower level (subsystems or agents) and the interactions at that level, lead to global behavior (complex system or multiagent system.) In this project, designer-subsystem pairs will be aligned with agents. Corresponding designer-subsystem objectives will then be derived based on system-level objectives while implicitly accounting for subsystem interactions. These objectives will replace the traditional intermediate design targets with principled objectives that, if met, ensure desired overall system performance. This project will aim to show that an approach based on objective functions, previously successfully applied to the operation of complex multiagent systems, can in a modified form also serve as an approach for the design of complex engineered systems.