Questions tagged [genetic-algorithms]
The genetic-algorithms tag has no usage guidance.
44
questions
7
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2answers
81 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:
...
0
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0answers
11 views
Best ways of encoding neural networks for GA
I am trying to create a genetic algorithm that should create optimal neural networks based on two parameters - network size and value of the fitness function, so that we can find networks that are ...
1
vote
1answer
11 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 4 outputs, corresponding to the probabilities of different actions. The neural network ...
0
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0answers
26 views
Basic questions about fitting a formula with gradient descent or genetic algorythm
I've been trying to code a following problem. I have defined a function depending on a number of parameters (in my case, those of a Bragg mirror and a x-ray beam). Now I am trying to compare the ...
0
votes
1answer
37 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 ...
0
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0answers
10 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:...
0
votes
0answers
10 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 ...
1
vote
1answer
14 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 ...
3
votes
0answers
89 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 (...
0
votes
1answer
37 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
1answer
25 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 ...
1
vote
2answers
29 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 ...
5
votes
3answers
529 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 ...
0
votes
1answer
41 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 ...
0
votes
0answers
11 views
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 ...
0
votes
0answers
19 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 ...
0
votes
0answers
23 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 ...
4
votes
1answer
62 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 ...
0
votes
2answers
142 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 ...
0
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0answers
19 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 ...
1
vote
1answer
206 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 ...
0
votes
1answer
29 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 ...
0
votes
1answer
61 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 ...
1
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0answers
45 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 ...
13
votes
2answers
777 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
votes
1answer
153 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
...
1
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0answers
350 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 ...
2
votes
2answers
104 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, ...
0
votes
1answer
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 ...
2
votes
1answer
4k 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?
1
vote
1answer
40 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 ...
1
vote
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 ...
3
votes
2answers
396 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,...
1
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0answers
44 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 ...
0
votes
1answer
429 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 ...
5
votes
1answer
579 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 ...
6
votes
4answers
4k 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 ...
4
votes
1answer
6k 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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0answers
103 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 ...
2
votes
2answers
852 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,...
7
votes
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 ...
3
votes
2answers
553 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 ...
0
votes
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 ...
0
votes
2answers
97 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 ...
