We investigate the problem of learning constraint satisfac-tion problems from an inductive logic programming perspective. Con-straint satisfaction problems are the underlying basis for constraint pro-gramming and there is a long standing interest in techniques for learningthese. Constraint satisfaction problems are often described using a rela-tional logic, so inductive logic programming is a natural candidate forlearning such problems. So far, there is however only little work on theintersection between learning constraint satisfaction problems and induc-tive logic programming. In this article, we point out several similaritiesand di↵erences between the two classes of techniques that may inspirefurther cross-fertilization between these two fields.