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A Pragmatic Guide to Building Conservative Discrete Abstractions of Cyber-Physical Systems
US & West ·
The tutorial addresses common pitfalls in building discrete abstractions of cyber-physical systems for verification: under-approximating state space, transitions, unsound pruning of degenerate behaviors, and improper specification lifting. It offers a pragmatic workflow that guarantees conservativeness while balancing pessimism and tractability.
Why it matters
Ensuring abstraction soundness is necessary for verifying control system properties, which is important for modeling and analysis of large-scale systems.
В Северной Осетии активно внедряют умные технологии для контроля дорожной сети. Камеры фиксируют нарушения, на трассах работают пункты весогабаритного контроля, а во Владикавказе создаётся цифровой двойник города. Пассажиры смогут отслеживать движение трамваев в приложении.
Industrial environments are increasingly characterized by the tight interaction among physical processes, communication infrastructures, and intelligent applications. In this context, Digital Twins (DTs) have emerged as a key technology for system analysis and optimization.
Growing automation makes collaborative robots work in more variable environments, increasing the need for adaptation. We propose a human-in-the-loop online training framework combining a digital twin (DT), reinforcement learning (RL), and human demonstrations.
