Past Research

In short, my past research can be splitted into two categories:

• Learning a model from an existing implementation. In my case, the model is an automaton extended with some external resources, such as timers. This learning process is active: we decide which execution we want to study. While it can be classified as machine learning, this research direction is not based on statistical methods.
• Modeling a system as a game played on a graph. More precisely, we assume that we have an unknown number of opponents and want to compute a strategy that is winning no matter the exact number of opponents.

More details will be written later.