# Questions tagged [genetic-algorithms]

A class of optimization algorithms inspired by (or emulating) biological evolution.

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### What are downsides to "genetic matching," particularly outside of causal inference settings?

Multivariate matching methods typically involve two steps. First the user computes $D$, a matrix of the multivariate distances between units. Second, the user applies a matching function (e.g., 1:1 ...
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### Can you penalize based on difference between training and testing error?

Is it a valid or useful technique to penalize the model based on the objective function + abs(training error - testing error). The error would probably have to be scaled. This seems useful, and I am ...
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### Mutation probability for simple and complex problems

Is It always better increase the mutation probability if the problem is more complex? I'm doing different experiments trying to check if a higher mutation probability helps to find a solution when the ...
1 vote
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### Can reparameterizing the parameters for DEoptim improve convergence: whether/how to do it? [closed]

DEoptim is described as DEoptim implements the Differential Evolution algorithm for global optimization of a real-valued function of a real-valued parameter vector as described in Mullen et al. (2011)...
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1 vote
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### Genetic Algorithm as engine for Variational Inference?

I'm curious if anyone has used, heard of, or otherwise considered using Genetic Algorithms as an engine for Variational Inference (VI)? My understanding of VI is that it's an optimization algorithm, ...
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1 vote
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### Tic tac toe AI, general questions

Tl;dr - Very new to AIs and neural networks, trying to make tic tac toe. Trying to use a genetic algorithm that plays against other AIs, and the looser leaves. They seem to never learn even to not ...
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1 vote
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### How pairs of actual parents are formed from the mating pool in NSGA-II?

I understand the general idea of how NSGA-II works, however even by reading the original article from Deb and al. (https://ieeexplore.ieee.org/document/996017), flow charts, and so on, I don't ...
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### Multi-objective optimization problem - fitness

my task is to find a solution for a multiobjective optimization problem, which has two objectives. I'm solving this with a genetic algorithm by using a fitness function, which works fine. My question ...
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### optimization of real values and binary, what is the difference

Many optimization packages provide several ways to find solutions, one of which is the choice between binary search and search for real values. I have a real binary search task, but the search ...
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### Single optimum parameter output for multi-objective optimization (genetic algorithms)

If this question is out of scope for this forum, before closing it please advise me on a better platform to ask my question! I'm very new to this field so apologies if my questions are not clear. I am ...
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### Create Fitness score/highscore with multiple variables

I am currently building a Neural network( + genetic algorithms) that learns to fly a 2D drone to a target. My goal is that it achieve all tasks as fast a possible but I want the drone to also fly ...
1 vote
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### Human interpretable Neural Networks?

Say I made Neural Network Trading Algorithm. How to understand what it does? Example How human would do the job. Human look at charts and thinks, and then develops an algorithm like "make ...
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### Ways to compare feature selection methods

Context: A hyperspectral image is taken (here Indiana Pines) which needs to be reduced to a lower dimension from 200 bands for this GSA is to be used. What will be possible metrics to grade various ...
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### Bayesian genetic algorithms?

I'm not sure that "Bayesian genetic algorithms" is a real term or even a concept in research. For a while now, I've preferred genetic algorithms as my go-to heuristic optimization technique, ...
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### Sampling from distribution parametrized by $\log(1-p)$ given $\log (p)$

The context for the problem is that I'm working with a modified genetic algorithm where the fitness score of each chromosome is given by a log-probability $\log(p) \in (-\infty, 0)$. Thus, I have a ...
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### Best Statistical Techniques for Order Sensitive Data

Problem I am writing a Genetic Algorithm (GA) that aims to find the best order of performing a given set of tasks to fulfill an objective. Imagine there are a set of tasks ...
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### What are the rules for evolving a partially connected neural network using a genetic algorithm?

I am working on a project where I need to implement the NEAT algorithm in python. after doing some research I came across an issue that I can't seem to find a solution for online, I hope this is the ...
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### is there only one correct weight and bias for neural network?

I solved the xor problem using neural network... but I'm really confused my neural network structure looks like this! the first result was like... and the second result was like... could there be ...
1 vote
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### How to minimise a quantity using a Genetic Algorithm

I'm somewhat new to Genetic Algorithms and I've been exploring the use of them to minimize a quantity (Y), where my optimum value is a small negative value. I've implemented an algorithm that has a ...
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### Can I use genetic algorithm without an *explicit* objective function?

I'm confused with the following topic. I have a simulator with 3 real parameters as input and 1 real parameter as output. I don't have a function representing the relation between the parameters and ...
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### Would a genetic algorithm be used for this type of scheduling optimization?

Let me preface this by saying I'm not an experienced data scientist/statistician so I apologize if this is trivial. My problem statement is as follows: There are N events that happen from time A to ...
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### Genetic algorithm - mutation

I was trying to understand the principle of a GA and implemented it myself for some games and always got to the following question; Usually the evolving of a generations works the following: testing ...
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### Train a neural network for tic tac toe with a genetic algorithm [duplicate]

I was trying to implement a genetic algorithm for the game 'tic tac toe'. How I am doing it at the moment is the following: Initiliaze 50 random networks Let each network play against each network. ...
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1 vote
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### How to modify a Genetic Algorithm to optimise dependent variables?

Say that I want to build a classifier that performs the following: Encode each feature from a dataset (X encodings available) Perform a number of computations on the encoded values (Y number of ...
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### Performing a uniform crossover of parents

I'm trying to do a crossover of two vectors in my program. There are two vectors, each a parent in a sense, and they're both a series of random binary digits (1's and 0's). My goal is to randomly ...
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