Abstract

Genetic algorithms are meta-heuristic algorithms based on the biological evolution. These algorithms are found to be useful for finding near to optimum results for the NP-category of problems. GA suffers with the disadvantage of premature convergence. The paper focuses on the implementation of various techniques of handling premature convergence and the statistical evaluation of the obtained results to identify the optimal method to the problem of grammar induction. General Terms Evolutionary Computations, Grammar Inference, Learning.

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