ARCH-COMP22 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants

Diego Manzanas Lopez, Matthias Althoff, Luis Benet, Xin Chen, Jiameng Fan, Marcelo Forets, Chao Huang, Taylor T. Johnson, Tobias Ladner, Wenchao Li, Christian Schilling, Qi Zhu

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations

Abstract

This report presents the results of a friendly competition for formal verification of continuous and hybrid systems with artificial intelligence (AI) components. Specifically, machine learning (ML) components in cyber-physical systems (CPS), such as feedforward neural networks used as feedback controllers in closed-loop systems are considered, which is a class of systems classically known as intelligent control systems, or in more modern and specific terms, neural network control systems (NNCS). We more broadly refer to this category as AI and NNCS (AINNCS). The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2022. In the fourth edition of this AINNCS category at ARCH-COMP, four tools have been applied to solve 10 different benchmark problems. There are two new participants: CORA and POLAR, and two previous participants: JuliaReach and NNV.

Original languageEnglish (US)
Pages (from-to)142-184
Number of pages43
JournalEPiC Series in Computing
Volume90
DOIs
StatePublished - 2022
Event9th International Workshop on Applied Verification of Continuous and Hybrid Systems, ARCH 2022 - Munich, Germany
Duration: Sep 5 2022Sep 5 2022

ASJC Scopus subject areas

  • General Computer Science

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