Context free grammar induction library using Genetic Algorithms

摘要

As we all are aware that "Evolutionary Algorithms" (EAs) are modern techniques used for searching for an optimum. One can establish communication via two medium first oral communications (Speech Processing) and second is written (Text Processing). This project focuses the second medium (text processing) of communication where we communicate using any language by writing some thing. Genetic Algorithms are developed as random search methods, which have not so sensitivity on primary data of the problems. It can be used in estimation of system parameter to get the best possible solution. Genetic Algorithms have been discussed for grammar induction. Grammar Inference or Language Learning is the process of learning grammar from training data. This paper mainly discussed the various methods for learning context-free grammar (CFG) from the corpus of string and presents the approach of informant learning in the form of result for two standard grammar problems first balanced parenthesis problem and second two symbol palindrome over {a, b}.