Adversarial Game

Adversarial games model interactions between competing agents, aiming to understand strategic decision-making under opposition. Current research focuses on applying this framework to diverse areas, including robotics, cybersecurity, and machine learning, often employing game-theoretic formulations and algorithms like reinforcement learning and generative adversarial networks (GANs) to analyze optimal strategies and model vulnerabilities. These studies are significant for improving the robustness and fairness of AI systems, enhancing security protocols, and providing insights into complex real-world scenarios involving competing interests.