PARSING UNCERTAIN CONTEXT-FREE LANGUAGES BY GENETIC ALGORITHMS

Abstract

The parsing of context free languages can be done by efficient algorithms in O(n3) for general context-free case and in O(n) for certain classes as LL and LR. All these algorithms are very strict, they fail to recover on any insignificant input error. In this paper we propose a robust parsing technique for uncertain inputs based on genetic algorithms. As the genetic techniques are computational expensive the genetic parser is not intended to substitute classical parser, but to assist it. During the parsing process, erroneous input words could be passed to the genetic parser in order to find the best approximation of the input word. The technique is parallelizable so that in a proper computing environment the problem of computing resource crunching can be surpassed.