alogos.systems.dsge.crossover

Crossover functions for DSGE.

Functions

gene_swap(grammar, genotype1, genotype2, parameters=None)

Generate new DSGE genotypes by exchanging a random gene.

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Detailed object descriptions

alogos.systems.dsge.crossover.gene_swap(grammar, genotype1, genotype2, parameters=None)

Generate new DSGE genotypes by exchanging a random gene.

Each DSGE genotype contains the same number of genes. Randomly select one gene and exchange it between the two genotypes.

Parameters:

• grammar (Grammar)

• genotype1 (Genotype) – Genotype of the first parent.

• genotype2 (Genotype) – Genotype of the second parent.

• parameters (dict or ParameterCollection, optional) – Following keyword-value pairs are considered by this function:

  • repair_after_crossover (bool): {True, False}

Returns:

• genotype1 (Genotype) – Genotype of the first child.

• genotype2 (Genotype) – Genotype of the second child.

References

• Software implementations by the authors of the approach

  • Python: dsge

    • core/sge.py: def crossover(p1, p2) is the implementation of the crossover operator

• Papers

  • Lourenço et al. in 2018: Structured Grammatical Evolution: A Dynamic Approach

    • p. 145: “It starts by creating a random binary mask and the offspring are created by selecting the parents genes based on the mask values. Recombination does not modify the lists inside the genes. This is similar to what happens with uniform crossover for binary representations.”