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.

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4
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2answers
319 views

Iteratively and adaptively increasing the network size during training

For an experiment that I'm working on, I want to train a deep network in a special way. I want to initialize and train a small network first, then, in a specific way, I want to increase network depth ...
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2answers
162 views

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-...
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2answers
96 views

Is there any research work that attempts to combine neuroevolution with deep reinforcement learning

Neuroevolution can be used to evolve a network's architecture (and weights, of course). Deep reinforcement learning, on the other hand, has been proven to be extremely powerful at optimising the ...
4
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2answers
85 views

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 ...
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0answers
35 views

What are some examples of tasks in which, currently, neuroevolution outperforms gradient-based approaches?

Note: I am NOT asking for general advantages of neuroevolution over standard approaches (e.g.: architecture search, parallelization), I am asking for examples of tasks in which, currently, ...
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0answers
31 views

How do I choose an appropriate fitness function and hyper-parameters to train a 7-DOF arm?

I am trying to train an ANN to control a 7 Degrees-Of-Freedom arm. It should reach a target avoiding a single obstacle. Given my modeling of the situation, my input layer is composed of 12 nodes: 5 ...
5
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3answers
247 views

Can neural networks evolve other neural networks?

Can neural networks change or evolve other neural networks? Also, could evolutionary algorithms be applied to evolve neural networks? For example, suppose that we have neural networks A and B. The ...
3
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1answer
46 views

How accurate are neuroevolution algorithms in modelling organism evolution?

How accurate are neuro-evolution algorithms (such as NEAT) in modelling real organism evolution?
4
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1answer
138 views

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 ...
2
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1answer
66 views

Why would someone use NEAT over other machine learning algorithms?

Why would someone use a neuroevolution algorithm, such as NEAT, over other machine learning algorithms? What situation would only apply to an algorithm such as NEAT, but no other machine learning ...
2
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0answers
35 views

Can neuroevolution be used for solving tasks other than games?

I'm seeing a lot of examples of neuroevolution techniques involving games or robot problems. Can neuroevolution be used for solving tasks other than games? For example, how could you transform a CSV ...
2
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1answer
85 views

Can NEAT produce neural networks where inputs are directly connected to outputs?

Can NEAT produce neural networks where inputs are directly (without intermediate hidden neurons) connected to outputs?
2
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1answer
408 views

What is the order of the genetic operations in NEAT?

I was trying to implement NEAT, but I got stuck at the speciating of my clients/genomes. What I got so far is: the distance function implemented, each genome can mutate nodes/connections, two ...
4
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1answer
2k views

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 ...
3
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1answer
165 views

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 ...
5
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2answers
586 views

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 ...
1
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1answer
357 views

Does neuroevolution require a labelled dataset?

A neuroevolution algorithm, such as DXNN, can be used to refine the topology and weights of an artificial neural network (ANN). The GA will require a fitness function, which means you need labeled ...
6
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4answers
247 views

What are some information processing models besides feedforward or multi-layered neural networks?

Feedforward or multilayered neural networks, like the one in the image above, are usually characterized by the fact that all weighted connections can be represented as a continuous real number. ...
5
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2answers
1k views

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?
6
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1answer
249 views

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. ...
5
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1answer
485 views

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 ...
5
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1answer
606 views

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 ...
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2answers
441 views

How do you choose the number of neurons, synapses, and hidden layers of an ANN (in NEAT)?

I want to make a Connect 4 AI using machine learning, but I'm a complete beginner to the topic. From what I've seen, an ANN is a way to go. Some phrases I've heard are "neuroevolution" and the acronym ...
4
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4answers
138 views

Is it possible to separately evolve a part of the population?

In a classic example of a genetic algorithm, you would have a population and a certain amount of simulation time to evaluate it and breeding. Then proceed to the next generation. Is it possible, ...
13
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2answers
361 views

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 ...
13
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2answers
575 views

How can I automate the choice of the topology 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 already existing topologies (perceptron, Konohen, etc) or I'm simply not aware of the existence of those or I'm ...