Questions tagged [genetic-algorithms]

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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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24 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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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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34 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 ...
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Unable to achieve expected results using Artificial Neural Networks & NEAT (Neuro Evolution of augmenting topologies) on 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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15 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 ...
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15 views

Selecting only the fittest chromosome for reproduction in genetic algorithms

Let's assume I track all my chromosomes with the fittness level in a database. The initial population will contain all available allels at least once. So, every solution exists at least in one ...
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1answer
46 views

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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1answer
17 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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17 views

Algorithm/Model for Power System Optimisation

For my engineering honours project, I'm performing a study of voltage control on the electrical distribution network, using reactive power provision from residential solar inverters. Basically, each ...
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0answers
18 views

What's the Advantage of Mutating the Activation Function?

I'm using NEAT (NeuroEvolution of Augmenting Technologies) as a genetic algorithm to evolve my neural network. One of the options in the configuration file for the python implementation of NEAT is to ...
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1answer
72 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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comparing genetic algorithm vs particle swarm optimization

I am trying out various optimization techniques. I would like to implement GA and PSO for the same optimization problem and compare them. I have found implementations for each with different examples. ...
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1answer
18 views

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

i'm new with the ga and i can't found specific info about the real coded ga, i want to do an antennas array optimization by using the real values of antennas position , phase and amplitude, but in my ...
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1answer
40 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 ...
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43 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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2answers
530 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 ...
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1answer
105 views

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 ...
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231 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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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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1k 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 ...
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1answer
2k views

Find the minimum value of x^2+y^2 with 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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1answer
37 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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2answers
2k 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 ...
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360 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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0answers
43 views

How effective is Genetic Algorithm for finding Attribute-Value relationships

I am implementing a module which finds based on user interactions on an online portal to find which attributes of a certain product and what values for those products influence the buyer to choose the ...
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1answer
390 views

selecting sample from population using genetic algorithm

I have a set of 31390 individuals with an associated weight (kg) and I want to select a number of them such that the maximum weight is 3000kgs and that the weight distribution around several variables ...
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1answer
543 views

Checkers playing Neural Network evolved with Genetic Algorithm becomes too sensitive to input data changes

I recently embarked on a very ambitious project and I have to say it has turned out a lot better than I expected, I succeeded in coding from scratch a neural network that plays checkers at a very ...
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4answers
3k views

Which book is a standard for introduction to genetic algorithms?

I have heard of genetic algorithms, but I have never seen practical examples and I've never got a systematic introduction to them. I am now looking for a textbook which introduces genetic algorithms ...
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1answer
5k views

What is the One Max Problem in detail?

I am looking a python lib named deap, but stuck at beginning. The first paragraph says: The problem is very simple, we search for a 1 filled list individual. ...
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99 views

Algorithm for rule set optimization

I have hand writed classifiers (there are a lot of them). It's implemented as collection of rule sets IIF - THEN. I want to optimize the % of errors. There some ...
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2answers
774 views

Understanding genetic algorithms

What is a genetic algorithm, and what are its practical advantages over other algorithms? Is it similar to any commonly used machine learning algorithm like linear/logistic regression, neural networks,...
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1answer
14k views

Simple example of genetic alg minimization

I have been looking for a while for examples of how I could find the points at which a function achieves its minimum using a genetic algorithm approach in Python. I looked at DEAP documentation, but ...
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2answers
499 views

Genetic Algorithm to find best parameter values of an estimaor

I am making some stochastic training ensemble classes in Python, and I want to get hyperparameters values. Grid search will take too long for moderate data sets, because in my stochastic training I ...
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1answer
1k views

Using the GA R package to optimize the weights of a MLP neural network

The neural network I am trying to evolve uses the tanh as an activation function in each neuron and has a topology of 1-5-1, so I need at least 5 weights. The solution of the GA is a real-number ...
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96 views

Data prediction book [closed]

While I was studying, few years ago , one of the most interesting topic was evolution, genetic algorithms and neural networks. Many of the problems I faced could be solved by using that knowledge. I ...