  Usage of automated controllers which make decisions on an environment are
widespread and are often based on black-box models. We use Knowledge
Compilation theory to bring explainability to the controller's decision given
the state of the system. For this, we use simulated historical state-action
data as input and build a compact and structured representation which relates
states with actions. We implement this method in a Traffic Light Control
scenario where the controller selects the light cycle by observing the presence
(or absence) of vehicles in different regions of the incoming roads.
