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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16 views

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 ...
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29 views

If artificial neural networks are a special case of computation graphs, so maybe let's optimize computational graphs rather than neural networks?

Existing ANNs are so good for solving complicated tasks on a different domain of data. But creating a neural network is always a hassle and its success mostly relies on an engineer's intuition and ...
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102 views

How to select good inputs and fitness function to achive good results with NEAT for Icy Tower bot

I'm trying to make a bot to the famous "Icy Tower" game. I rebuilt the game using pygame and I'm trying to build the bot using Python-NEAT. Every generation a population of 70 characters tries to ...
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21 views

Can operations like convolution and pooling be discovered with a neural architecture search approach?

From Neural Architecture Search: A Survey, first published in 2018: Moreover, common search spaces are also based on predefined building blocks, such as different kinds of convolutions and ...
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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 ...
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1answer
34 views

Do I have to crossover my node genes in NEAT, and how?

I'm currently trying to code the NEAT algorithm by myself, but I got stuck with two questions. Here they are: What happens if during crossover a node is removed (or disabled) and there's a connection ...
2
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1answer
72 views

How to choose the activation function in neuroevolution?

I am developing a NEAT flappy bird game, and it doesn't work, the system stays stupid for 300 generations. I chose tanh() for activation, just because it's included in JS. I can't find a good ...
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2answers
53 views

Are connections genes in a genome ever deleted or just disabled?

When a new node is added, the previous connection is disabled and not removed. Is there any situation in which a connection gene is removed? For example, in the above diagram connection gene with ...
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1answer
44 views

What are evolutionary algorithms for topology and weights evolving of ANN (TWEANN) other than NEAT?

I wonder, if there are other than NEAT approaches to evolving architectures and weights of artificial neural networks? To be more specific: I am looking for projects/frameworks/libraries that use ...
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1answer
44 views

How are weights updated in a genetic algorithm with neural network?

Suppose an AI is to play the game flappy bird. And the fitness function is how long the bird has traveled before the game ends. Would we have multiple neural networks initialized at the beginning ...
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1answer
57 views

Unable to achieve expected outputs using NEAT for the snake game

I am trying to implement NEAT for the snake game. My game logic is ready, which is working properly and NEAT configured. But even after 100 generations with 200 genomes per generation, the snakes ...
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2answers
324 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
301 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
248 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 ...
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3answers
188 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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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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43 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 ...
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3answers
291 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 ...
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1answer
52 views

How accurate are neuroevolution algorithms in modelling organism evolution?

How accurate are neuro-evolution algorithms (such as NEAT) in modelling real organism evolution?
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1answer
156 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 ...
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1answer
115 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 ...
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0answers
37 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 ...
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1answer
130 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?
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1answer
531 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 ...
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1answer
522 views

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 ...
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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 ...
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1answer
207 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 ...
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2answers
506 views

Can mutation enable a disabled connection?

In the add node mutation, the connection between two chosen nodes (e.g. A and B) is first disabled and then a new node is created between A and B with their respective two connections. I guess that ...
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2answers
788 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 ...
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1answer
132 views

In novelty search, are the novel structures or behaviour of the neural network rewarded?

I have been reading a lot lately about some very promising work coming out of Uber's AI Labs using mutation algorithms enhanced with novelty search to evolve deep neural nets. See the paper Safe ...
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2answers
371 views

How does adjusted fitness penalize large species in NEAT?

I'm learning about NEAT from the paper Evolving Neural Networks through Augmenting Topologies. I'm having trouble understanding how adjusted fitness penalizes large species and prevents them from ...
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1answer
378 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 ...
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4answers
311 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. ...
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2answers
2k 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?
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1answer
300 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. ...
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1answer
522 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 ...
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1answer
727 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
489 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 ...
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4answers
139 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, ...
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2answers
415 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 ...
14
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2answers
629 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 ...