<p>In genetic algorithms, mutation without crossover simply means that part of the population is randomly changed. In this case this is applied to 25% of the population.</p>

<p>The remaining 75% either remain unchanged (generally the best performing specimen), or will be combined with other specimen (using crossover). It's a bit more complex here, as the genome is connecting weights in networks, and they use 'species', where certain individuals are treated as separate groups from the rest of the population.</p>

CC BY-SA 4.0
2020-04-18T18:00:44.933Z
2020-04-18T18:00:44.933Z
Oliver Mason
<p>I am reading through the <a href="http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf" rel="nofollow noreferrer">NEAT paper</a>. In parameter settings, page 15, there is:</p>

<blockquote>
  <p>In each generation, 25% of offspring resulted from mutation without crossover.</p>
</blockquote>

<p>What does it mean?</p>

<papers><neat><crossover-operators><mutation-operators><genetic-operators>
What does "In each generation, 25% of offspring resulted from mutation without crossover" mean in the context of NEAT?
galaxy001
# What does "In each generation, 25% of offspring resulted from mutation without crossover" mean in the context of NEAT?

(Asked by: username_0 on 2020-04-18)

I am reading through the [NEAT paper](http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf). In parameter settings, page 15, there is:

> In each generation, 25% of offspring resulted from mutation without crossover.

What does it mean?

**Tags:** papers, neat, crossover-operators, mutation-operators, genetic-operators


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## 1 answers

### Answer by username_1 on 2020-04-18. Score: 2 | Accepted answer

In genetic algorithms, mutation without crossover simply means that part of the population is randomly changed. In this case this is applied to 25% of the population.

The remaining 75% either remain unchanged (generally the best performing specimen), or will be combined with other specimen (using crossover). It's a bit more complex here, as the genome is connecting weights in networks, and they use 'species', where certain individuals are treated as separate groups from the rest of the population.


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