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Questions tagged [genetic-operators]

For questions related to genetic operators, such as the selection, crossover or mutation operators.

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Less mutation rate is performing better in bigger neural network

I have a genetic AI neural network that evolves every generation and can add or remove neurons and change weights. It evolves good in first generations with mutation rate probability of e.g. ...
Mahdyfo's user avatar
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Which of these 3 mutation rates is the best in terms of performance?

I am need some comments since I am conducting experiments with 3 different mutation rates and hesitate to choose the best one. I ...
LearningLogic's user avatar
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how to apply crossover and mutation rates in genetic algorithm?

I'm working with genetic programming and let's say I have the following operator: pop_size = 100 Crossover ratio = 0.4 Mutation Ratio = 0.2 Selection Ratio = 0.1 What is exactly the next generation ...
CTMA's user avatar
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Would it be a good idea to mutate half of the offspring of each GA generation 100% of the time and the other half 0% of the time?

I was reading about genetic algorithms, and to my understanding a genetic algorithm (GA) is an algorithm that starts with an initial population of chromosomes, where each chromosome has associated ...
Joseph Walker's user avatar
2 votes
1 answer

What is the impact of changing the crossover and mutation rates?

What is the impact of using a: low crossover rate high crossover rate low mutation rate high mutation rate
fathese's user avatar
  • 131
1 vote
1 answer

Is there some known pattern for selecting a batch of candidates for the next generation?

I'm a beginner with a classic "racing car" sandbox and a homemade simple neural network. My pattern: Copy the "top car" (without mutation) to the next generation If there are ...
ker2x's user avatar
  • 163
3 votes
2 answers

Can we use genetic algorithms to evolve datasets?

Genetic algorithms are used to solve many optimization tasks. If I have a dataset, can I evolve it with a genetic algorithm to create an evolved version of the same dataset? We could consider each ...
Souradip Roy's user avatar
2 votes
3 answers

How to avoid running out of solutions in genetic algorithm due to selection?

The genetic algorithm consists of 5 phases of which 4 are repeated: Initial population (initially) Fitness function Selection Crossover Mutation In the selection phase, the number of solutions ...
MScott's user avatar
  • 445
3 votes
2 answers

How do I determine the genomes to use for crossover in NEAT?

If I have the fitness of each genome, how do I determine which genome will crossover with which, and so on, so that I get a new population? Unfortunately, I can't find anything about it in the ...
GastUser's user avatar
2 votes
1 answer

How does the crossover operator work when my output contains only 2 states?

I'm currently working on a project where I am using a basic cellular automata and a genetic algorithm to create dungeon-like maps. Currently, I'm having an incredibly hard time understanding how ...
Ryan's user avatar
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What does "In each generation, 25% of offspring resulted from mutation without crossover" mean in the context of NEAT?

I am reading through the NEAT paper. In parameter settings, page 15, there is: In each generation, 25% of offspring resulted from mutation without crossover. What does it mean?
galaxy001's user avatar
  • 103
5 votes
4 answers

What is the difference between "mutation" and "crossover"?

In the context of evolutionary computation, in particular genetic algorithms, there are two stochastic operations "mutation" and "crossover". What are the differences between them?
Abbas Ali's user avatar
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Does fitness proportionate selection select multiple individuals?

Does fitness proportionate selection select multiple individuals? So, I read on Wikipedia and on multiple Stack Exchange threads about fitness proportionate selection or rather roulette selection, but ...
Philogy's user avatar
  • 201
11 votes
2 answers

How do mutation and crossover work with real-valued chromosomes?

How exactly are "mutation" and "cross-over" applied in the context of a genetic algorithm based on real numbers (as opposed to just bits)? I think I understood how those two phases are applied in a "...
danidemi's user avatar
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2 votes
1 answer

What is meant by "reproduction" in the description of this exercise?

In the following exercise, the word reproduction is mentioned. Your task is to design a simple genetic algorithm, with binary-coded chromosomes, in order to solve a pattern-finding problem in 16-bit ...
user avatar
9 votes
3 answers

Why is cross-over a part of genetic algorithms?

Genetic Algorithms has come to my attention recently when trying to correct/improve computer opponents for turn-based strategy computer games. I implemented a simple Genetic Algorithm that didn't use ...
Mithical's user avatar
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