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Questions tagged [genetic-algorithms]

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49 views

Why is my genetic algorithm overfitting so much?

I'm only training on a fraction of the data each generation: ...
• 111
25 views

Matlab genetic algorithm for instances selection problem with no convergence

This is my test using matlab ga function for instances selection or training set selection. As you can see I used a simplified dataset to be sure of the performance. You can see it in the first lines ...
14 views

How to set boundaries for Primitives in Genetic Programming

my question is very simple. How can I set the boundaries to the primitives of a Genetic Programming Algo? Le's make an example: I want as primitive the square root of a number, we know very well that ...
25 views

What (ML) algorithms take an image as input and optimal action as output?

I have a given 2d image describing a top down view of a grid (think e.g. a labirynth.) I want an algorithm to take it as an input and return a single action to be performed in the setting of this grid....
1 vote
22 views

What is the meaning of selection probability in genetic algorithm with roullete selection method

I am studying an article about implementation of genetic algorithm. Here is the parameters which are used in this article: As I know, in roullete selection method, probability of selecting ...
1 vote
22 views

Are there any algorithm to generate a set of data that match some statistic requirements?

I was wondering if there are time-efficient algorithms that can reverse the process of basic statistics computation. What I mean is an algorithm that instead of computing the mean, SD, max-min range, ...
• 13
58 views

Implementation/Optimization of Genetic Algorithm

I have a few queries regarding my implementation of the Genetic Algorithm (GA). I have a lot of parameters in which I have to find the best combination of these parameters to maximize the value of the ...
403 views

Are genetic algorithms considered to be generative models?

My understanding is that these sorts of algorithms can evolve/mutate data to hone in on specific desirable areas in large/difficult to search parameter spaces. Assuming one does this successfully, how ...
686 views

Genetic Algorithms (Specifically with Keras)

I can't get my deep genetic algorithm snake game to work and I can't figure out why. At this point, I think it must be either the crossover_rate/mutation_rate or the actual crossover code itself is ...
• 133
1 vote
19 views

Is there a multi-modal population based metaheuristic that is non-GA?

I have a feature set from which I want to select various combinations and permutations of the features. The length of a solution feature vector can range between , say 5 - 20 features , and the ...
• 11
1 vote
104 views

Best way to optimize problem with additively separable fitness function?

I am using a genetic algorithm to maximize a few hundred thousand real-valued variables. Each of the variables, $x_i$, has its own independent boundary condition. The fitness function uses each of ...
• 127
1 vote
17 views

Framework for Genetic Algorithms on python [duplicate]

I'm trying to use a framework implemented in python to use GA (Genetic algorithms) and other related algorithms . But I'm not sure about what framework to use, I've found two interesting options Pymoo ...
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181 views

Which Algorithm did OpenAI used to create a hide and seek playing Agent?

I just saw this video on youtube: https://www.youtube.com/watch?v=kopoLzvh5jY&t=9s Which Algorithm did OpenAI used to create a hide and seek playing Agent? Was it Genetic Algorithm or Policy ...
1 vote
595 views

Are there any tree-based models that use a genetic algorithm to generate the trees?

I have a large dataset (195 features x 20m samples) that I have trained using XGBoost. I would like to see if a genetic algorithm can beat XGBoost since the data has so much noise it is prone to ...
111 views

On what principle did Google's DeepMind learn to walk?

I just saw this video on Youtube. On what principle did Google's DeepMind learn to walk? Was it Q-Learning or a Genetic Algorithm or Policy Gradient?
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Drug Making Using Genetic Algorithms

I want to create a drug using N different chemicals for fighting a bacterial infection those N chemicals are contained inside the drug in different quantities my work environment is a simulated one ...
1 vote
64 views

Why use gradient descent on Deep Nets / RNNs when cost function is not convex?

Why do we use gradient descent on very non-convex loss functions such as in Deep nets / RNNs rather than a heuristic search (genetic algorithms, simulated annealing, etc)?
1 vote
98 views

Good chromosome representation in a VRPTW genetic algorithm

I have a genetic algorithm for a vehicle routing problem with time windows and I need to implement certain modifications. I am not sure what would be the best chromosome representations. I have tasks ...
281 views

use genetic algorithm as a feature selection for text classification

how to apply the genetic algorithm as a feature selection for text classification in python I need to use GA to select most relevant feature in text classification
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1k views

Creating a generic mathematical formula using a genetic algorithm

Assuming all of the following; I have 4 known numbers, all within a 0-400 range, like this: ...
202 views

Parameter initialization in a genetic algorithm

I'm using a neural network in a genetic algorithm. The neural network has 4 inputs (values between 0 and 1) and ...
124 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 ...
131 views

How do I use matrix math in irregular neural networks such as those generated from neuroevolution (NEAT)?

I understand how to structure the matrix when every node in a layer is fully connected to every node in adjacent layers and I understand that in "irregular" neural networks I can just process each ...
1 vote
12 views

Basket items optimisation minimising constraints

I have a real problem (not home work) when I have to distribute an ordered list by position to respect some constraints eg. 1. 11 2. 15 3. 18 4. 18 5. 1 baskets:...
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1 vote
39 views

optimize integers using GA package

The GA package is a great package to use Genetic Algorithm for optimization. See for example this. I have a use case, where my possible values are integer (e.g. 1, 2, 4 ...). So far, I simply rounded ...
• 174
1 vote
84 views

Genetic Optimization, Heuristic regarding choosing the number of generations and population size

I have a simple model with some fitness function that I'm trying to max out. This model have ~20 variables, each about ~15 options. Is there a heuristic formula or a study of some sort that can guide ...
• 115
260 views

Ising Spin Glass - Optimization

I'm a newbie researcher working on model-based genetic algorithms, mainly linkage learning in both discrete and continuous spaces, using data modeling. I would like to ask you about Ising Spin Glass (...
• 834
77 views

Genetic algorithm only using selection

Suppose you have a population of N individuals with fitness 1, 2, . . . , N (i.e., all individuals have a unique fitness value). Suppose you repeatedly apply ...
1 vote
152 views

Why GA convergence curves continue as two parallel lines?

I'm working on a optimization problem and using GA algorithm (in MATLAB, ga function). As you know MATLAB plots GA result with two curves, one for the best values and other to show the mean values ...
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1 vote
60 views

Universal function approximation with fixed values (as vector or matrix)

I was thinking about way to represent/approximate universal function and came up with the idea that a plain fixed numbers could be used to represent pretty much any function on a fixed interval. I ...
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638 views

Genetic algorithms(GAs): to be considered only as optimization algorithms? Are GAs used in machine learning any way?

As a quick question, what are genetic algorithms meant to be used for? I read somewhere else that they should be used as optimization algorithms (similar to the way we use gradient descent to optimize ...
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157 views

Genetic algorithms: what connection to support vector machine / naive bayes

I found the following list of seven classifiers: Linear Classifiers: Logistic Regression, Naive Bayes Classifier Nearest Neighbor Support Vector Machines Decision Trees Boosted Trees Random ...
43 views

Will it be more computationally expensive to have multipl 2d tensors or 1 3d tensor

Odd question but I am busy creating a Genetic Algorithm that optimizes the weights on a Neural Network instead of using good old fashion 1st-order optimization (Gradient/Adam) What I have is x as a ...
• 135
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Mutation on demand in genetic algorithms

genetic algorithm usually use a "mutation rate" to control the rate of chromosome mutation. Most of the researchers at researchgate recommend to keep this rate low in order to converge quickly, to be ...
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1 vote
2k views

Python metaheuristic packages

I need to use a metaheuristic algorithm to solve an optimization problem on a Python codebase. Metaheuristics usually need to be written in C++ or Java as they involve a lot of iterations, while ...
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1 vote
2k views

What should I study to find optimal value of best feature combinations in machine learning?

I would like to do production optimization with machine learning and/or optimization problem. My goal is not to find minimizing loss in loss function only to give the best y value. My ultimate goal ...
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134 views

What's the correct form of use the real coded genetic algorithm?

I'm new to genetic algorithms, but I haven't found specific info about real-coded GA's. I want to do antenna array optimization by using the real values of antenna position, phase, and amplitude, but ...
1 vote
527 views

What makes a problem good for an evolutionary strategy vs a genetic algorithm vs particle swarm optimization?

I understand that evolutionary strategies (ES), genetic algorithms (GA), and particle swarm optimization (PSO) are all algorithms used to solve optimization types of problems, but what might make an ...
• 111
1 vote
114 views

In which cases should Genetic Programming be preferred over Artificial Neural Network trained with Genetic Algorithm

I am trying to understand Genetic Programming (GP) but I cannot think of any context where GP can be chosen over training Artificial Neural Networks with genetic algorithms. What problems each of ...
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2k views

Why aren't Genetic Algorithms used for optimizing neural networks?

From my understanding, Genetic Algorithms are powerful tools for multi-objective optimization. Furthermore, training Neural Networks (especially deep ones) is hard and has many issues (non-convex ...
• 413
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What is new population in genetic algorithm?

Here is my (mis?)understanding of genetic algorithm: Create n individuals. This is initial population Calculate fitness of each individual in this population ...
1 vote
1k views

Neuroevolution library/framework with GPU CUDA support

I'm looking for working library/framework allowing you to use neuroevolution algorithms like NEAT with GPU support (CUDA). Are there any working libraries? I know about AccNEAT library but I couldn't ...
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189 views

Is deduction, genetic programming, PCA, or clustering machine learning according to Tom Mitchells definition?

Tom M. Mitchell defines machine learning as A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, ...
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1 vote
3k views

Is it possible to use NEAT networks for solving video games?

Sorry to start such an unspecific question, but I am slightly lost in the big topic. My tutor proposed to chose neural networks for my final project, and we started by building a CNN for detecting ...
7k views

How do I find the minimum value of $x^2+y^2$ with a genetic algorithm?

I want to find $(x,y)$ which minimizes $x^2+y^2$ with GA to apply it for another function. Does anyone know any example of GA with deap (Python) like that?
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1 vote
57 views

Gene innovation numbers in NEAT implementatoins

In NEAT (neuroevolution through augmenting topologies) algorithm description, an innovation number, e.g. id, is assigned to each gene so that genomes can be crossed over meaningfully: genes having ...
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5k views

Can I have a neural network output values >100?

All the samples and articles i have seen are all having outputs of 1 or less. Is there a hidden reason why no one is using NN to produce higher value integers?? My situation is that I want NN to ...
523 views

Genetic neural network to satisfy variable number of inputs and outputs

I have what I propose as a solution to my problem, however I haven't ever seen it mentioned in this way, so I worry that there is a valid reason not to do things this way. I have a dataset of > 100,...
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