Inductive Classification Logic (ICL in short) is a ILP learning system that learns first order logic formulae from examples which belong to two or more classes. The learned theory can be used to classify unseen examples. Examples are viewed as (Herbrand) interpretations. These are assumed be specified completely (we also say that we learn from closed examples). So ICL performs discriminating induction from closed examples. | 
