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StocHy: automated verification and synthesis of stochastic processes

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arxiv 1901.10287 v1 pith:UYRRJT32 submitted 2019-01-29 eess.SY cs.SY

classification eess.SYcs.SY
keywords stochyallowsstochasticsynthesistoolverificationabstractionseasily
verification ladder T0 review T1 audit T2 compute T3 formal
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StocHy is a software tool for the quantitative analysis of discrete-time stochastic hybrid systems (SHS). StocHy accepts a high-level description of stochastic models and constructs an equivalent SHS model. The tool allows to (i) simulate the SHS evolution over a given time horizon; and to automatically construct formal abstractions of the SHS. Abstractions are then employed for (ii) formal verification or (iii) control (policy, strategy) synthesis. StocHy allows for modular modelling, and has separate simulation, verification and synthesis engines, which are implemented as independent libraries. This allows for libraries to be easily used and for extensions to be easily built. The tool is implemented in C++ and employs manipulations based on vector calculus, the use of sparse matrices, the symbolic construction of probabilistic kernels, and multi-threading. Experiments show StocHy's markedly improved performance when compared to existing abstraction-based approaches: in particular, StocHy beats state-of-the-art tools in terms of precision (abstraction error) and computational effort, and finally attains scalability to large-sized models (12 continuous dimensions). StocHy is available at www.gitlab.com/natchi92/StocHy.

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  1. Scalable control synthesis for stochastic systems via structural IMDP abstractions

    eess.SY 2024-11 conditional novelty 6.0 of 10

    A new abstraction model, odIMDP, stores transition probabilities as products of per-dimension interval bounds, cutting memory and conservatism in stochastic controller synthesis.

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