ARCH-COMP23类别报告:随机模型

Alessandro Abate, Henk Blom, Nathalie Cauchi, Joanna Delicaris, Sofie Haesaert, Birgit van Huijgevoort, Abolfazl Lavaei, Anne Remke, Oliver Schön, Stefan Schupp, Fedor Shmarov, Sadegh Soudjani, Lisa Willemsen, Paolo Zuliani
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引用次数: 0

摘要

本报告关注随机模型的正式验证和政策综合的友好竞争。该报告的主要目标是在这一类别中引入新的基准及其属性,并为明年的比赛提出建议。考虑到与非概率模型相比,随机模型的工具处于开发的早期阶段,主要焦点是报告收集所有这些工具可以运行的一组最小基准的主动性,从而促进实现技术之间的效率比较。这项友好竞赛是2023年夏季连续和混合系统(ARCH)应用验证研讨会的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ARCH-COMP23 Category Report: Stochastic Models
This report is concerned with a friendly competition for formal verification and policy synthesis of stochastic models. The main goal of the report is to introduce new benchmarks and their properties within this category and recommend next steps toward next year’s edition of the competition. Given that the tools for stochastic models are at their early stages of development compared to those of non-probabilistic models, the main focus is to report on an initiative to collect a set of minimal benchmarks that all such tools can run, thus facilitating the comparison between the efficiency of the implemented techniques. This friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in Summer 2023.
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