Altering Search Rates of the Meta and Solution Grammars in the mGGA

  • Erik Hemberg
  • Michael O’Neill
  • Anthony Brabazon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4971)


Adopting a meta-Grammar with Grammatical Evolution(GE) allows GE to evolve the grammar that it uses to specify the construction of a syntactically correct solution. The ability to evolve a grammar in the context of GE means that useful bias towards specific structures and solutions can be evolved during a run. This can lead to improved performance over the standard static grammar in terms of adapting to a dynamic environment and improved scalability to larger problem instances. This approach allows the evolution of modularity and reuse both on structural and symbol levels resulting in a compression of the representation of a solution. In this paper an analysis of altering the rate of sampling of the evolved solution grammars is undertaken. It is found that the majority of evolutionary search is currently focused on the generation of the solution grammars to such an extent that the candidate solutions are often hard-coded into them making the solution chromosome effectively redundant. This opens the door to future work in which we can explore how the search can be better balanced between the meta and solution grammars


Mutation Rate Problem Instance Fitness Evaluation Evolutionary Search Grammatical Evolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Erik Hemberg
    • 1
  • Michael O’Neill
    • 1
  • Anthony Brabazon
    • 1
  1. 1.Natural Computing Research & Applications GroupUniversity College DublinIreland

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