An Adversarial Agent-Based Design Method Using Stochastic Stackelberg Game Conditions
Abstract
Products must often endure challenging conditions while fulfilling their intended functions. Game-theoretic methods can readily create a wide variety of these conditions to consider when creating designs. This work introduces Cognitively Inspired Adversarial Agents (CIAAs) that use a Stackelberg game format to generate designs resistant to these conditions. These agents are used to generate designs while considering a multidimensional attack. Designs are produced under these adversarial conditions and compared to others generated without considering adversaries to confirm the agents’ performance. The agents create designs able to withstand multiple combined conditions.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 29, 2021
- Source ID
- 10.1115/1.4049862
Entities
People
- Christopher McComb
- Jonathan Cagan
- Sean C. Rismiller
Organizations
- Carnegie Mellon University
- Defense Advanced Research Projects Agency
- Pennsylvania State University