# Uppaal Coshy: Automatic Synthesis of Compact Shields for Hybrid Systems

arXiv: https://arxiv.org/abs/2508.16345 · HTML: https://mlsanity.com/paper/2508.16345/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 22 references that are in the map.
- First posted on arXiv 22 Aug 2025.

## Builds on (most cited first, 9 of 9)

- [Safe Reinforcement Learning via Shielding](https://mlsanity.com/paper/1708.08611/) (2017)
- [Techniques for Interpretable Machine Learning](https://mlsanity.com/paper/1808.00033/) (2018)
- [MurTree: Optimal Classification Trees via Dynamic Programming and Search](https://mlsanity.com/paper/2007.12652/) (2020)
- [dtControl 2.0: Explainable Strategy Representation via Decision Tree Learning Steered by Experts](https://mlsanity.com/paper/2101.07202/) (2021)
- [TEMPEST -- Synthesis Tool for Reactive Systems and Shields in Probabilistic Environments](https://mlsanity.com/paper/2105.12588/) (2021)
- [dtControl: Decision Tree Learning Algorithms for Controller Representation](https://mlsanity.com/paper/2002.04991/) (2020)
- [Shielded Reinforcement Learning for Hybrid Systems](https://mlsanity.com/paper/2308.14424/) (2023)
- [Efficient Shield Synthesis via State-Space Transformation](https://mlsanity.com/paper/2407.19911/) (2024)
- [In Search of Trees: Decision-Tree Policy Synthesis for Black-Box Systems via Search](https://mlsanity.com/paper/2409.03260/) (2024)

## Built on by (most cited first, 1 of 1)

- [dtControl2+varepsilon: Trading Optimality for Explainability in MDPs via Decision Trees](https://mlsanity.com/paper/2607.25925/) (2026)

## Abstract (arXiv)

We present Uppaal Coshy, a tool for automatic synthesis of a safety strategy -- or shield -- for Markov decision processes over continuous state spaces and complex hybrid dynamics. The general methodology is to partition the state space and then solve a two-player safety game, which entails a number of algorithmically hard problems such as reachability for hybrid systems. The general philosophy of Uppaal Coshy is to approximate hard-to-obtain solutions using simulations. Our implementation is fully automatic and supports the expressive formalism of Uppaal models, which encompass stochastic hybrid automata. The precision of our partition-based approach benefits from using finer grids, which however are not efficient to store. We include an algorithm called Caap to efficiently compute a compact representation of a shield in the form of a decision tree, which yields significant reductions.