Uppaal Coshy: Automatic Synthesis of Compact Shields for Hybrid Systems

2025-08-22

AI Summary

Synthesizing safe, compact shielding policies for Markov decision processes (MDPs) with continuous state spaces and complex hybrid dynamics remains challenging. Method: We propose Caap, a simulation-driven framework that models the system as a stochastic hybrid automaton, constructs an approximate two-player safety game via adaptive gridding-based state-space abstraction, and computes its winning region. A decision-tree compression technique is then applied to distill the high-dimensional safety policy into a compact, symbolic, and interpretable representation. Contribution/Results: Unlike conventional exact model-checking approaches, Caap provides formal safety guarantees while drastically reducing computational cost and memory footprint. It enables automated shield synthesis for expressive models—such as those supported by Uppaal—without sacrificing accuracy. Caap thus unifies precision, efficiency, and policy compactness, advancing scalable and verifiable runtime assurance for hybrid systems.

Technology Category

• Humans and AI: Human-Aware Planning and Behavior Prediction
• Multiagent Systems: Multiagent Systems under Uncertainty
• Reasoning under Uncertainty: Sequential Decision Making

Application Category

• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Security and Privacy: Security and privacy of machine learning and AI applications
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

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.

Problem

• Synthesizing safety shields for hybrid Markov decision processes
• Solving reachability problems in complex hybrid system dynamics
• Compacting shield representations to reduce storage inefficiency

Innovation

• Automatic synthesis of safety strategies using simulations
• Partitioning state space to solve safety games
• Compact shield representation via decision trees