5 papers
Tolerance of Reinforcement Learning Controllers against Deviations in Cyber Physical Systems
Changjian Zhang, Parv Kapoor, Eunsuk Kang +5
Cyber-physical systems (CPS) with reinforcement learning (RL)-based controllers are increasingly being deployed in complex physical environments such as autonomous vehicles, the In…
Safe Planning through Incremental Decomposition of Signal Temporal Logic Specifications
Parv Kapoor, Eunsuk Kang, Romulo Meira-Goes
Trajectory planning is a critical process that enables autonomous systems to safely navigate complex environments. Signal temporal logic (STL) specifications are an effective way t…
User-Driven Adaptation: Tailoring Autonomous Driving Systems with Dynamic Preferences
Mingyue Zhang, Jialong Li, Nianyu Li +2
In the realm of autonomous vehicles, dynamic user preferences are critical yet challenging to accommodate. Existing methods often misrepresent these preferences, either by overlook…
Integrating Graceful Degradation and Recovery through Requirement-driven Adaptation
Simon Chu, Justin Koe, David Garlan +1
Cyber-physical systems (CPS) are subject to environmental uncertainties such as adverse operating conditions, malicious attacks, and hardware degradation. These uncertainties may l…
Investigating Robustness in Cyber-Physical Systems: Specification-Centric Analysis in the face of System Deviations
Changjian Zhang, Parv Kapoor, Romulo Meira-Goes +5
The adoption of cyber-physical systems (CPS) is on the rise in complex physical environments, encompassing domains such as autonomous vehicles, the Internet of Things (IoT), and sm…