Intelligent systems are often called upon to form plans that direct their own or other agents' activities. For these systems, the ability to describe plans to people in natur...
We propose a symbolic algorithm for the analysis of the robustness of timed automata, that is the correctness of the model in presence of small drifts on the clocks or imprecision ...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Automated verification is a technique for establishing if certain properties, usually expressed in temporal logic, hold for a system model. The model can be defined using a high-l...
In transfer learning we aim to solve new problems using fewer examples using information gained from solving related problems. Transfer learning has been successful in practice, a...