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Individual representations

Genetic Engine currently supports 4 individual representations:

  • Tree-based representation, also known as Context-Free Grammars GP (CFG-GP)1
  • Grammatical Evolution (GE)2
  • Structured GE (SGE)3
  • Dynamic SGE (dSGE)4

The representation can be chosen by the user. There are many discussions on which representation performs better as a search algorithm (fitness progression will differ across algorithms). Genetic Engine uses the same method for tree generation in CFG-GP and genotype-to-phenotype mapping in GE, SGE and dSGE, making it individual-representation independent on the implementation side. Still, we aim to implement performance enhancements on trees, benefitting the performance of CFG-GP, both on the time performance side (such as detailed in 5), as on the algorithm side.

Tree-based

.. autoapiclass:: geneticengine.representations.tree.treebased.TreeBasedRepresentation

Grammatical Evolution

.. autoapiclass:: geneticengine.representations.grammatical_evolution.ge.GrammaticalEvolutionRepresentation

Structured Grammatical Evolution

.. autoapiclass:: geneticengine.representations.grammatical_evolution.structured_ge.StructuredGrammaticalEvolutionRepresentation

Dynamic Structured Grammatical Evolution

.. autoapiclass:: geneticengine.representations.grammatical_evolution.dynamic_structured_ge.DynamicStructuredGrammaticalEvolutionRepresentation

Stack-based Grammatical Evolution

.. autoapiclass:: geneticengine.representations.stackgggp.StackBasedGGGPRepresentation

Custom Representations

To create a custom representation, you just need to subclass the following abstract class:

.. autoapiclass:: geneticengine.representations.api.Representation

To support Genetic Programming, you also need to implement:

.. autoapiclass:: geneticengine.representations.api.RepresentationWithMutation

.. autoapiclass:: geneticengine.representations.api.RepresentationWithCrossover
References

Footnotes

  1. Whigham, Peter A. "Grammatically-based genetic programming." Proceedings of the workshop on genetic programming: from theory to real-world applications. Vol. 16. No. 3. 1995. ↩

  2. Ryan, Conor, John James Collins, and Michael O. Neill. "Grammatical evolution: Evolving programs for an arbitrary language." European conference on genetic programming. Springer, Berlin, Heidelberg, 1998. ↩

  3. Lourenço, Nuno, Francisco B. Pereira, and Ernesto Costa. "SGE: a structured representation for grammatical evolution." International Conference on Artificial Evolution (Evolution Artificielle). Springer, Cham, 2015. ↩

  4. Lourenço, Nuno, et al. "Structured grammatical evolution: a dynamic approach." Handbook of Grammatical Evolution. Springer, Cham, 2018. 137-161. ↩

  5. Ingelse, Leon, et al. "Benchmarking Representations of Individuals in Grammar-Guided Genetic Programming." Evo* 2022: 5. ↩