Structuring Chromosomes for Context-Free Grammar Evolution

This paper investigates the use of genetic algorithms for inferring small regular and context-free grammars. Applied simply, a genetic algorithm is not very effective at this. To overcome this problem we investigate two methods of structuring the chromosomes. The rst is to bias the distribution of`1's in the population of chromosomes according to an algebraic expansion technique previously developed by the author. This`design' of the chromosome distribution , shows no bias to any particular type of language (i.e. full generality is retained) yet improves convergence. The second method involves performing the evolution (i.e. making the mutations) in a diierent space, where the grammars are represented inèm-bedded normal form'. The latter approach structures the chromosome to represent context-free rather than regular grammars, for example. It is shown that biasing the chromosome in this fashion produces extremely fast convergence, and 3-symbol palindromes grammars are learned in typically less than 10 generations .