Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [neuroevolution]

For questions related to neuroevolution (or neuro-evolution) techniques, such as NEAT, that are used to evolve (or train) artificial neural networks (that is, they are used evolve their parameters or topology), inspired by the natural evolution. A neuroevolution algorithm is thus an evolutionary algorithm where the genomes (individuals or chromosomes) are artificial neural networks.

See e.g. https://en.wikipedia.org/wiki/Neuroevolution.

63 questions
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How can I automate the choice of the architecture of a neural network for an arbitrary problem?

Assume that I want to solve an issue with a neural network that either I can't fit to existing architectures (perceptron, Konohen, etc) or I'm simply not aware of the existence of those or I'm unable to understand their mechanics and I rely on my…
Zoltán Schmidt
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How should I encode the structure of a neural network into a genome?

For a deterministic problem space, I need to find a neural network with the optimal node and link structure. I want to use a genetic algorithm to simulate many neural networks to find the best network structure for the problem domain. I've never…
Mithical
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What if the more fit parent has fewer nodes compared to the other, will the disjoint and excess genes be discarded?

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…
Neil Nahid
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Does training happen during NEAT?

When one uses NEAT to evolve the best fitting network for a task, does training take place in each epoch as well? If I understand correctly, training is the adjustment of the weights of the neural network via backpropagation and gradient descent.…
Alexus
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How does mating take place in NEAT?

In the Evolving Neural Networks through Augmenting Topologies (NEAT) paper it says (p. 110): The entire population is then replaced by the offspring of the remaining organisms in each species. But how does it take place? Are they paired and then…
Miemels
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In NEAT, is it a good idea to give the same ID to node genes created from the same connection gene?

Do I have to prevent nodes created from the same connection gene to have different IDs/innovation number? In this example, the node 6 is created from the connection going from node 3 to node 4: In the case where that specific node was already…
Dara Kong
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Can neuroevolution be combined with gradient descent?

Is there any precedent for using a neuroevolution algorithm, like NEAT, as a way of getting to an initialization of weights for a network that can then be fine-tuned with gradient descent and back-propagation? I wonder if this may be a faster way…
benbyford
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Several questions regarding the NEAT algorithm

I've recently read the paper Evolving Neural Networks through Augmenting Topologies which introduces NEAT. I am now trying to prototype it myself in JavaScript. However, I stumbled across a few questions I can't answer. What is the definition of…
Nigk
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Does NEAT require only connection genes to be marked with a global innovation number?

Does NEAT require only connection genes to be marked with a global innovation number? From the NEAT paper Whenever a new gene appears (through structural mutation), a global innovation number is incremented and assigned to that gene. It seems…
kuma
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Is it possible to classify data using a genetic algorithm?

Is it possible to classify data using a genetic algorithm? For example, would it be possible to sort this database? Any example in Matlab?
Ricardo Pouças
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What happens if 2 genes have the same connection but a different innovation number?

I have read the Evolving Neural Networks through Augmenting Topologies (NEAT) paper, but some doubts are still bugging me, so I have two questions. When do mutations occur? Between which nodes? When mating, what happens if 2 genes have the same…
Miemels
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When do mutations in NEAT occur?

I read through the Evolving Neural Networks through Augmenting Topologies (NEAT) paper. I understand the algorithm now, but one thing is still unclear to me. When does the mutation occur and how does it take place? How is it chosen whether to add a…
Miemels
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Why evolutionary training of neural networks is not popular?

Evolutionary algorithms are mentioned in some sources as a method to train a neural network (finding weights, not hyperparameters). However, I have not heard about one practical application of such an idea yet. My question is, why is that? What are…
GKozinski
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How is neural architecture search performed?

I have come across something that IBM offers called neural architecture search. You feed it a data set and it outputs an initial neural architecture that you can train. How is neural architecture search (NAS) performed? Do they use heuristics, or is…
Adam Geringer
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Is there a neural network with a varying number of neurons?

Is there some type of neural network that changes the number of neurons while training? Using this idea, the network can increase or decrease the number of neurons when the complexity of the inputs increases or decreases.
Aura Lee
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