Questions tagged [genetic-algorithms]
The genetic-algorithms tag has no usage guidance.
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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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0answers
40 views
How to use genetic algorithm to generate association rules from a transaction dataset using Python?
Please help! I really need to use GA to obtain association rules.
My dataset looks like this:
...
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0answers
15 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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1answer
31 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 ...
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1answer
54 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 ...
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1answer
34 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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1answer
35 views
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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0answers
60 views
What is explicit fitness sharing in NEAT?
I cannot understand what is explicit fitness sharing. Could someone explain it?
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2answers
45 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)?
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1answer
37 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 ...
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90 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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2answers
156 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:
...
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1answer
50 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 ...
2
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1answer
62 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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1answer
88 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 ...
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0answers
11 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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0answers
15 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 ...
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1answer
16 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 ...
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0answers
166 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 (...
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1answer
59 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 ...
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1answer
41 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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2answers
38 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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3answers
571 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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1answer
53 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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0answers
23 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 ...
4
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1answer
69 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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2answers
900 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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1answer
610 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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1answer
61 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 ...
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1answer
240 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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1answer
73 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
1k 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 ...
0
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1answer
323 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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0answers
592 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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2answers
133 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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1answer
2k 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
5k 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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1answer
47 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
4k 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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2answers
451 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
45 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
452 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
644 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
5k 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
8k 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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1answer
108 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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3answers
1k 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
15k 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
614 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
2k 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 ...
