We are developing techniques and software to formally verify AI-based systems, building upon the PRISM toolset.
We are working on techniques and tools for verification and strategy synthesis with stochastic games, built into the PRISM-games tool. Recent advances includes methods for concurrent stochastic games and temporal logics and synthesis for equilibria.
Papers: [CAV'20] [QEST'20] [FMSD-21] [TACAS'22] [ARCRAS-22] [MFCS'22] [QEST'23]
We are developing techniques to verify deep reinforcement learning systems, whose controllers are learnt and represented as deep neural networks.
Papers: [FORMATS'20] [IJCAI'21] [NFM'22]
We are building robust methods for verification and control of stochastic systems in the presence of epistemic uncertainty.
We are developing techniques for verified probabilistic control unde partial observation, including for: