Grammatical optimization is based on an idea to provide production rules of a user specified context-free grammar (in Backus-Naur form) to a genetic algorithm. The genetic algorithm works on the back end as a solution finder. The production rules are used to map the genomes of the GA to a computer program. So basically, to cut it short, grammatical evolution is a way to create computer programs as potential solutions of a user-specified problem. The evolutionary search of the GA guides the overall solution to some form of optimal points. In recent variants a GA can be replaced with other search techniques such as particle swarm optimization.
This project is an implementation of the grammatical evolution (GE) framework. It is basically a hack of the original GE framework implemented in C++ by the BDS group of the university of Limerick. It is implemented in Java. It is named grammatical optimization because it is aimed at being more general. To this end, this means that it does not necessarily require a genetic algorithm as a search algorithm to be run on the back end. On the other hand, any nice search technique, such as particle swarm optimization can also be used. The source code of grammatical optimization can be found here.
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