Reinforcement learning (RL) is a powerful approach for training agents t...
Deep Neural Networks (DNN) are becoming increasingly more important in
a...
Recursion is the fundamental paradigm to finitely describe potentially
i...
When omega-regular objectives were first proposed in model-free reinforc...
Reinforcement learning synthesizes controllers without prior knowledge o...
We study reinforcement learning for the optimal control of Branching Mar...
Binary decision diagrams can compactly represent vast sets of states,
mi...
We provide the first solution for model-free reinforcement learning of
ω...
Parametric Markov chains occur quite naturally in various applications: ...
The analysis of parametrised systems is a growing field in verification,...