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ARCH-COMP23 Category Report: Stochastic Models

25 pagesPublished: October 18, 2023

Abstract

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.

Keyphrases: control synthesis, formal verification, Markov chains, Markov Decision Processes, stochastic models

In: Goran Frehse and Matthias Althoff (editors). Proceedings of 10th International Workshop on Applied Verification of Continuous and Hybrid Systems (ARCH23), vol 96, pages 126--150

Links:
BibTeX entry
@inproceedings{ARCH23:ARCH_COMP23_Category_Report_Stochastic,
  author    = {Alessandro Abate and Henk Blom and Nathalie Cauchi and Joanna Delicaris and Sofie Haesaert and Birgit van Huijgevoort and Abolfazl Lavaei and Anne Remke and Oliver Sch\textbackslash{}"on and Stefan Schupp and Fedor Shmarov and Sadegh Soudjani and Lisa Willemsen and Paolo Zuliani},
  title     = {ARCH-COMP23 Category Report: Stochastic Models},
  booktitle = {Proceedings of 10th International Workshop on Applied Verification of Continuous and Hybrid Systems (ARCH23)},
  editor    = {Goran Frehse and Matthias Althoff},
  series    = {EPiC Series in Computing},
  volume    = {96},
  pages     = {126--150},
  year      = {2023},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/xZ8M},
  doi       = {10.29007/k7s6}}
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