Learning grammars with a modified classifier system

This paper describes a modified learning classifier system for evolving grammars from small, handcrafted grammars. The algorithm uses distinct discovery and evaluation steps, and a culling step to reduce ambiguity. It performs surprisingly well in developing grammars for very complex sentences in a restricted domain of English, and in some experiments the grammar's competence improved up to tenfold.