Learning classifier system approach to natural language grammar induction

This paper describes an evolutionary approach to the problem of inferring non-stochastic context-free grammar (CFG) from natural language (NL) corpora. The approach employs Grammar-based Classifier System (GCS). GCS is a new version of Learning Classifier Systems in which classifiers are represented by CFG in Chomsky Normal Form. GCS has been tested on the NL corpora, and it provided comparable results to the pure genetic induction approach, but in a significantly shorter time. The efficient implementation for grammar induction is very important during analysis of large text corpora.