Architectural Transformations and Emerging Verification Demands in AI-Enabled Cyber-Physical Systems
It tackles verification challenges for AI-enabled CPS, which is an incremental contribution focusing on domain-specific systems.
The paper investigates how AI integration transforms the architecture and verification needs of Cyber-Physical Systems, comparing AI-driven and traditional control models in Simulink to address gaps in understanding operational complexity.
In the world of Cyber-Physical Systems (CPS), a captivating real-time fusion occurs where digital technology meets the physical world. This synergy has been significantly transformed by the integration of artificial intelligence (AI), a move that dramatically enhances system adaptability and introduces a layer of complexity that impacts CPS control optimization and reliability. Despite advancements in AI integration, a significant gap remains in understanding how this shift affects CPS architecture, operational complexity, and verification practices. The extended abstract addresses this gap by investigating architectural distinctions between AI-driven and traditional control models designed in Simulink and their respective implications for system verification.