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In the paper Efficient Evolution of Neural Network Topologies (2002), the authors say

Genes that do not match are inherited from the more fit parent

What if the more fit parent has fewer nodes compared to the other, will the disjoint/excess genes be discarded?

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  • $\begingroup$ yes, the only disjoint and excess genes that are used in crossover are from the more fit parent, any disjoint/excess genes from the less fit parent are disregarded $\endgroup$ – nickw Nov 7 '19 at 15:06
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When crossover happens and one parent is fitter than the other, the nodes from the more fit parent are carried over to the child. This is the case as disjoint and excess genes are only carried over from the fittest parent. Here's an example:

// Node Crossover
Parent 1 Nodes: {[0][1][2]} // more fit parent
Parent 2 Nodes: {[0][1][2][3]}

Child Nodes:    {[0][1][2]} // after crossover

Gene information is also passed to the child during crossover. Matching genes (those that have the same innovation number) are chosen at random and passed to the child. The disjoint and excess genes are choose from the more fit parent.

// Gene Crossover
Parent 1 Genes: [1][2][3]      [6]   [8][9][10] // more fit parent
Parent 2 Genes: [1][2][3][4][5]   [7]

Child Genes: [1][2][3][6][8][9][10] // after crossover

As you can see, the gene innovation numbers in the child match up with the innovation numbers of the fittest parent. However the gene information from matching genes (in the example genes 1, 2 and 3 match) have an equal chance of being carried over to the child. In the example, the child's first three genes could have come from either parent.

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