Stochastic stackelberg games for agent-driven robust design

Sean C. Rismiller, Jonathan Cagan, Christopher McComb

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Products must often endure unpredictable and challenging conditions while fulfilling their intended functions. Gametheoretic methods make it possible for designers to design solutions that are robust against complicated conditions, however, these methods are often specific to the problems they investigate. This work introduces the Game-Augmented Robust Simulated Annealing Teams (GARSAT) framework, a gametheoretic agent-based architecture that generates solutions robust to variation, and models problems with elementary information, making it easily extendable. The platform was 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 created robust designs able to withstand multiple combined conditions, and the effects of the adversarial settings on the designs were explored.

Original languageEnglish (US)
Title of host publication46th Design Automation Conference (DAC)
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791884003
DOIs
StatePublished - 2020
EventASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2020 - Virtual, Online
Duration: Aug 17 2020Aug 19 2020

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume11A-2020

Conference

ConferenceASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2020
CityVirtual, Online
Period8/17/208/19/20

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

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