Answers.Body: <p>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:</p>
  <pre><code>// 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
  </code></pre>
  <p>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 chose from the more fit parent.</p>
  <pre><code>// 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
  </code></pre>
  <p>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.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-05-09T16:12:19.357Z
Answers.LastActivityDate: 2021-12-23T00:09:39.617Z
Answers.LastEditDate: 2021-12-23T00:09:39.617Z
Answers.UserDisplayName: Chris
Body: <p>In the paper <a href="http://nn.cs.utexas.edu/downloads/papers/stanley.cec02.pdf" rel="nofollow noreferrer">Efficient Evolution of Neural Network Topologies</a> (2002), the authors say </p>
  
  <blockquote>
    <p>Genes that do not match are inherited from the more fit parent</p>
  </blockquote>
  
  <p>What if the more fit parent has fewer nodes compared to the other, will the disjoint/excess genes be discarded?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-07T15:06:55.803Z
Comments.Text: 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
Comments.UserDisplayName: nickw
Tags: <neural-networks><machine-learning><neat><neuroevolution><papers>
Title: What if the more fit parent has fewer nodes compared to the other, will the disjoint and excess genes be discarded?
UserDisplayName: Neil Nahid
ThreadText: # What if the more fit parent has fewer nodes compared to the other, will the disjoint and excess genes be discarded?
  
  (Asked by: username_0 on 2018-05-07)
  
  In the paper [Efficient Evolution of Neural Network Topologies](http://nn.cs.utexas.edu/downloads/papers/stanley.cec02.pdf) (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?
  
  **Tags:** neural-networks, machine-learning, neat, neuroevolution, papers
  > **Comments:**
  > **username_1**: 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  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2018-05-09. Score: 7 | Accepted answer
  
  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 chose 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.
  
  
  ---
  
  