Critical Scenario

"Critical scenario" research focuses on identifying and analyzing situations where systems or processes face significant failure or disruption, aiming to improve resilience and safety. Current research employs diverse methods, including optimization models (e.g., Ant Colony optimization), large language models (e.g., LLMs like Gemini), and machine learning techniques (e.g., supervised and unsupervised learning, contrastive learning) to detect, predict, and mitigate these scenarios across various domains. This work has significant implications for improving the robustness of autonomous systems, enhancing disaster preparedness, and developing more reliable and ethical AI systems.