Questions tagged [genetic-algorithms]
The genetic-algorithms tag has no usage guidance.
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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, ...
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Initialization Methods for the first Population in genetic algorithm for solivng the multiple traveling salesman problem
I am trying to compare the performance of several initialization methods for genetic optimization to solve a multiple traveling salesman problem. I have already the implementations for random and ...
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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 ...
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How to perform crossover between models of different sizes in deep genetic algorithms?
I'm working building a genetic algorithm that will learn to play snake. I've worked out how to add/remove layers and neurons in the model, allowing the model's size to change through mutation. But ...
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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 ...
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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 ...
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how is grammatic evolution different from grammar-based genetic programming?
There are two closely related techniques in genetic programming. One of them is grammar based genetic programming (GBGP), which uses context free grammar to generate a derivative tree which represents ...
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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 ...
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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 ...
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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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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 ...
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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 ...
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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 ...
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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)?
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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 ...
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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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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:
...
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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 ...
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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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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 ...
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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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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 ...
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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 ...
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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 (...
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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 ...
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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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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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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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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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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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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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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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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 ...
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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