Products must often endure unpredictable and challenging conditions while fulfilling their intended functions. Game-theoretic methods make it possible for designers to create solutions that are robust against complicated conditions during the design process, however, these methods are often specific to the problems they investigate. This work introduces the Game-Augmented Robust Simulated Annealing Teams (GARSAT) framework, a game-theoretic agent-based architecture to model problems with elementary information, allowing for extendibility, and generate solutions robust to variation. The platform is used to generate designs under consideration of a multidimensional attack. Designs were produced under various adversarial settings and compared to designs generated without considering adversaries to validate the model. The process successfully creates robust designs able to withstand multiple combined conditions, and the effects of various adversarial settings on the designs were explored.


Stochastic Stackelberg Games for Agent-Driven Robust Design

Division / Sponsors: 
Design Engineering Division and Computers & Information In Engineering Division


Paper Proceedings: https://asmedigitalcollection.asme.org/IDETC-CIE/IDETC-CIE2020/volume/83907

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