Stochastic hybrid systems have received significant attentions as a relevant modeling
framework describing many systems, from engineering to the life sciences: they enable the …

Timed automata are a common formalism for the verification of concurrent systems subject to
timing constraints. They extend finite-state automata with clocks, that constrain the system …

This paper concerns the efficient construction of a safety shield for reinforcement learning.
We specifically target scenarios that incorporate uncertainty and use Markov decision …

We present a major new release of the PRISM-games model checker, featuring multiple
significant advances in its support for verification and strategy synthesis of stochastic games …

Reinforcement learning algorithms discover policies that maximize reward. However, these
policies generally do not adhere to safety, leaving safety in reinforcement learning (and in …

We present an extensive collection of quantitative models to facilitate the development,
comparison, and benchmarking of new verification algorithms and tools. All models have a …

Formal methods encompass a wide choice of techniques and tools for the specification,
development, analysis, and verification of software and hardware systems. Formal methods …

With many applications across domains as diverse as logistics, healthcare, and agriculture,
service robots are in increasingly high demand. Nevertheless, the designers of these robots …

Traffic signal control plays a pivotal role in reducing traffic congestion. Traffic signals cannot
be adequately controlled with conventional methods due to the high variations and …

Reinforcement Learning (RL) is a widely employed machine learning architecture that has
been applied to a variety of control problems. However, applications in safety-critical …