The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/2c221b54-a20b-4659-99d2-af4a9a114b60

Mathiesen, Frederik Baymler; Haesaert, Sofie; Laurenti, Luca (2025): Data and code underlying the publication: Scalable control synthesis for stochastic systems via structural IMDP abstractions. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/2c221b54-a20b-4659-99d2-af4a9a114b60.v1

Categories

• Computation Theory and Mathematics
• Information and Computing Sciences

Keywords

Embedded systems Markov processes Stochastic control and optimization

Licence

MIT

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by Frederik Baymler Mathiesen , Sofie Haesaert , Luca Laurenti

This dataset is a repeatability evaluation package for the paper "Scalable control synthesis for stochastic systems via structural IMDP abstractions", Frederik Baymler Mathiesen, Sofie Haesaert, Luca Laurenti, 2024. The core idea is to verify properties about stochastic dynamical systems by finding a finite-state representation, called an abstraction, which may more easily be verified. The repeatability package includes experiments of abstracting different types of stochastic systems (additive linear/affine, polynomial, neural network dynamic models, Gaussian processes, and stochastically switched systems) to Interval Markov Decision Processes (IMDPs), orthogonally decoupled IMDPs (odIMDPs), and mixtures of odIMDPs. odIMDPs are a new abstract model proposed in the paper, where the ambiguity sets of transition probabilities are specified as products of (marginal) interval ambiguity sets.

The dataset includes all benchmark instances, a Docker-based command-line interface, plotting and table generating code, code for comparison against baseline tools IMPaCT and SySCoRe. For instructions on how to run the package, please consult the README.md file of the dataset.

History

• 2025-01-30 first online, published, posted

Publisher

4TU.ResearchData

Format

text/markdown, text/julia, text/matlab, text/cpp, application/json, image/png

References

• https://arxiv.org/abs/2411.11803

Code hosting project url

https://github.com/Zinoex/IntervalMDPAbstractions.jl

Organizations

TU Delft, Faculty of Mechanical Engineering, Delft Center for Systems and Control
TU Eindhoven, Department of Electrical Engineering