Empirical game theoretic system and method for adversarial decision analysis
US12223430B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 8, 2021 |
| Grant date | Feb 11, 2025 |
| Priority date | — |
| Expiry date | Dec 13, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described is a system for performing a simulated vehicle control task based on adversarial decision analysis. Empirical game theoretic analyses are performed between an evolving and an adversary population of neural network strategies. Each empirical game theoretic analysis includes using a neuroevolution procedure to perform a fitness-based selection of a strategy in the evolving population that out-performs the adversary population. Using an empirical game theory procedure, the neuroevolution procedure is iteratively run and the selected strategy is added to the adversary population with each iteration, resulting in monotonic strategy improvement with each iteration. Following the empirical game theoretic analyses, a final strategy is selected for the evolving population and the adversary population using a tournament selection procedure. The final strategy is used to train a neural network which is used to perform a simulated vehicle control task.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.