Marina de la Cruz López
ABSTRACT
Grammar-guided genetic programming is a type of genetic programming that uses a grammar to restrict the solutions in the exploration of the search space. Different representations of grammar-guided genetic programming exist, each with specific properties that affect how the evolutionary process is developed. We propose a new representation that uses a tree structure with non-encoding nodes for the individuals in the population, a.k.a. Tree-Based Grammatical Evolution with Non-Encoding Nodes. Each tree's node has a set of children nodes and an associated number that determines which are used in decoding the solution and which are non-encoding nodes. This representation increases the size and complexity of the individuals while performing a more exhaustive exploration of the solution space. We compare the performance of our proposal with state-of-the-art genetic programming algorithms for the 11-multiplexer benchmark, showing encouraging results.
- Ian Dempsey, Michael O'Neill, and Anthony Brabazon. 2009. Grammatical Evolution. Springer Berlin Heidelberg, Berlin, Heidelberg, 9--24. Google Scholar
Cross Ref
- Nuno Lourenço, Filipe Assunção, Francisco Pereira, Ernesto Costa, and Penousal Machado. 2018. Structured grammatical evolution: A dynamic approach. 137--161. Google ScholarCross Ref
- P.A. Whigham. 1999. Grammatically-based Genetic Programming. (06 1999).Google Scholar
Index Terms
- Tree-Based Grammatical Evolution with Non-Encoding Nodes
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