Questions tagged [genetic-algorithms]

For questions related to genetic algorithms (GAs), which are a form of evolutionary algorithms. A genetic algorithm is a method (more precisely, a metaheuristic) for solving optimization and search problems based on natural selection processes (that is, they use bio-inspired operators such as mutation, crossover, and selection).

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Metrics of quality of parameter space exploration

Considering a black box optimization problem on non-linear, non-convex function where we want to minimize an objective function. One way to assess the quality of an optimizer is to look at the best ...
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CNN - Visualizing images near decision boundary - Pixels inexplicably tend to edges

We are exploring the images classified by a CNN at its decision boundary, using Genetic Algorithms to generate them. We have created a fine-tuned binary grayscale image classifier for cats. As the ...
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Library for rendering neural network NEAT

I just finished my implementation of NEAT and I want to see the phenotype of each genome. Is there a library for displaying a neural network like this? Example of my genome syntax: ...
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How can I solve the linkage problem in genetic algorithms?

In a genetic algorithm, the order of the genes on a chromosome can have a significant effect on the performance (capacity to generate adaptation) of the genetic algorithm, where two or more genes ...
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Is a neural network the correct approach to optimising a fitness function in a genetic algorithm?

I've written an application to help players pick the optimal heroes during the draft phase of the Heroes of the Storm MOBA. It can be daunting to pick from 80+ characters that have synergies/counters ...
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2answers
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Can neuroevolution be combined with gradient descent?

Is there any precedent for using a neuroevolution algorithm, like NEAT, as a way of getting to an initialization of weights for a network that can then be fine-tuned with gradient descent and back-...
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1answer
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Disabling of genes during crossover (NEAT)

I am implementing NEAT (Neuroevolution of augmenting topologies) by Stanley, Original Paper. I am facing a problem during crossover of genomes. Suppose two networks with connections ...
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1answer
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Can we automate the choice of the hyper-parameters of the evolutionary algorithms?

Certain hyper-parameters (e.g. the size of the offspring generation or the definition of the fitness function) and the design (e.g. how the mutation is performed) of evolutionary algorithms usually ...
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Can we use the Tierra approach to optimize machine code?

Thomas Ray's Tierra is a computer program which simulates life. In the linked paper, he argues how this simulation may have real-world applications, showing how his digital organisms (computer ...
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Exploding population size in neat-python

I am trying to make my AI win the board game "Catan" against my friends. Therefore i am using the python implementation of NEAT. As I changed the values of ...
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What qualifies as 'fitness' for a genetic algorithm that minimizes an error function?

Suppose I have a set of data that I want to apply a segmented regression to, fitting linearly across the breakpoint. I aim to find the offsets and slopes of either line and the position of the ...
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How does NEAT find the most successful generation without gradients?

I'm new to NEAT, so, please, don't be too harsh. How does NEAT find the most successful generation without gradient descent or gradients?
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Can we evolve 0 and 1?

Is it possible to combine or create conditional statements of 0 and 1, and optimize with an evolutionary algorithm (given that all computers use a binary system)? There may be an algorithm that maps ...
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How to implement a neural network for Flappy Bird in Python?

I am new in the field of AI. I am working to create the flappy bird using Genetic Algorithm. After reading and seeing some examples, I saw that most implementations use a Neural Network + Genetic ...
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How to find optimal mutation probability and crossover probability?

I have a genetic algorithm that maximizes a fitness function with two variables f(X,Y). I have been running the algorithm with various parameters in mutation and crossover probability (0.1, 0.2, ...) ...
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Shortest route GA: One loop through one dataset vs multiple loops through subsets of the same data?

I've a rather simple question for a school project. We're developing a GA solution for the following problem: Chromosome: A location with lat-lon coords. There are two types of locations - up to 15 ...
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52 views

Is there a reason evolutionary algorithms are language-bound in research material?

I've been working on genetic algorithms & evolutionary strategies for a while now in a research context. Across the vast majority of the articles and content I've read, every single one of them ...
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Applications of genetic algorithms in project management

Do you see any GA Application that could support Project Management? I thought about Task Dispatching. I am curious about your ideas.
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Judging a genetic algorithm's priority-based schedules by how far ahead the higher priority things are done

I'm creating a schedule for a summer camp. Because of the high risk of rain, the higher priority activities need to be attempted first, so there is more time for later attempts if need be (temporarily ...
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How do I write a genetic algorithm to solve the knapsack problem?

I am trying to write a genetic algorithm that generates 100 items, assigning random weights and utilities to them. And then try to pick items how out these 100 items while maximising the utility and ...
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1answer
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How to handle infeasiblity caused due to crossover and mutation in genetic algorithm for optimization

I have chromosomes with floating point representation with values between 0 and 1. For example- Let ...
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What is the genetic algorithm for? [duplicate]

I am new in the field of genetic algorithms, and I want to learn to use them in practice. How the genetic algorithm work and why it is applied ?
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Stereo matching using genetic algorithm

I have been reading a few papers (paper1, paper2) on stereo matching using genetic algorithms. I understand how genetic algorithms work in general and how stereo matching works, but I do not ...
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Genetic algorithm: How to crossover 2D permutation?

Each chromosome contains an array of genes, each gene contains a letter and a number, both letter and number can only exist once in each chromosome. ...
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1answer
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Using NEAT, will the child of two parent genomes always have the same structure as the more fit parent?

I'm trying to implement the NEAT Algorithm using c#, based off of Kenneth O. Stanley's paper. On page 109 (12 in the pdf) it states "Matching genes are inherited randomly, whereas disjoint genes (...
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When should I use simulated annealing as opposed to a genetic algorithm?

What kind of problems is simulated annealing better suited for compared to genetic algorithms? From my experience, genetic algorithms seem to perform better than simulated annealing for most problems....
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Genetic Algorithm vs Particle Swarm Optimization

Which one gives better optimization results? Genetic Algorithm or Particle Swarm Optimization? Can I use them for online tuning problems? Thanks in advance!
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why we apply mutation after getting offspring in genetic algorithm?

When we get the offspring and fitness so why we prefer to apply mutation in genetic algorithm?
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Scrabble game using machine learning

I've been thinking if machine learning can be used to play the game Scrabble. My knowledge is limited in the ML field, thus I've seeking some pointers :) I want to know how could I possibly build a ...
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1answer
571 views

How to calculate fitness function of 8-queens problem?

In evolutionary computation and in particular in the context of genetic algorithms, there is a stochastic operation called "fitness function". The better a state, the greater the value of the fitness ...
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How to create a good fitness function?

In genetic algorithms, a function called "fitness" (or "evaluation") function is used to determine the "fitness" of the chromosomes. Creating a good fitness function is one of the challenging tasks in ...
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1answer
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How can a genetic algorithm adapt and get better in a changing environment?

I've just started studying genetic algorithms and I'm not able to understand why a genetic algorithm can improve if, at each learning, the 'world' that the population encounters change. For example, ...
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105 views

Selection methods in genetic algorithms

In genetic algorithm, there are different steps. One of those steps is selection of chromosomes for reproduction (Evolution). In this step there are different methods are used for selection of ...
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What is the difference between “mutation” and “crossover”?

In the context of evolutionary computation, in particular genetic algorithms, there are two stochastic operations "mutation" and "crossover". What are the differences between them?
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What kind of algorithm can invent?

Set aside networks, image classification, gradients, and the strength of intelligence for a moment and consider the world before people lit fires. Fires were started periodically just as they are now,...
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Do genetic algorithm and neural networks really think?

I'm aware of those AI programmes which can play games and neural networks which can identify pictures. But are they really thinking. Do they think like humans? Do they have consciousness? Or are they ...
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How to use Genetic Algorithm for varying lengths of solutions

Until now, I always thought that Genetic Algorithm can be used for problems of which the solution space can be encoded (modeled) as a chromosome of a specific length. However, some people claim that ...
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Spontaneous emergence of replicators in Artificial Life

One of the corner stones of The Selfish Gene (Dawkins) is the spontaneous emergence of replicators, i.e. molecules capable of replicating themselves. Has this been modeled in silico in open-ended ...
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173 views

Fitness function in genetic algorithm based on an interval

I am writing an app, where when a ball is shot from a canon it is supposed to land in a hole which is on a given distance. The ball is supposed to land between the distance of the begining of the hole ...
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3answers
212 views

Do intelligent systems make mistakes?

The intelligence of the human brain is said to be a strong factor leading to human survival. The human brain functions as overseer for many functions the organism requires. Like that, the most ...
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2answers
164 views

Representation of real numbers in Genetic Algorithm

Take a look at section 2.2.2 of this book (from Page-15 to 16). 2.2.2 Representation and Evaluation $$max f (x)= x sin(10πx)+2.0 ... ... ... (2.8)$$ $$s.t. −1 ≤ x ≤ 2$$ We can use a ...
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Learning Genetic algorithm for beginners

What is the best and easiest programming language to learn to implement Genetic algorithms? C++ or Python or any other?
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NEAT + Keras : reproducibility problem (World Models implementation)

I'm trying to apply the World Models architecture to the Sonic game (using the gym-retro library). My problem concerns the evolutionnary algorithm part that I use as the controller (worldmodels = ...
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1answer
195 views

How to optimize a function using a genetic algorithm?

I recently learned about Genetic algorithms and I solved the 8 queens problem using a genetic algorithm but I don't know how to optimize any functions using a genetic algorithm. I want a guide on how ...
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3answers
267 views

Can genetic algorithms be used to learn to play multiple games of the same type?

Is it possible for a genetic algorithm + Neural Network that is used to learn to play one game such as a platform game able to be applied to another different game of the same genre. So for example, ...
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1answer
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Genetic Algorithms: Trade-off between time and variance with regards to fitness function

I'm developing an AI to play a card game with a genetic algorithm. Initially, I will evaluate it against a player that plays randomly, so there will naturally be a lot of variance in the results. I ...
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1answer
96 views

Can neuro-evolution methods be combined with A3C?

As a amateur researcher and tinkerer, I've been reading up on neuro-evolution networks (e.g. NEAT) as well as the A3C RL approach presented by Mnih et al and got to wondering if anyone has ...
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How can I calculate MBF in genetic algorithms?

I've just started to learn genetics algorithms and I have found these measurements of runs that I don't understand: MBF: The mean best fitness measure (MBF) is the average of the best fitness ...
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Genetic Algorithm to Play Arkanoid(Nes) Possible Crossover and Fitness?

I am using the Fceux emulator to create a Genetic Algorithm in Lua to play the 'Arkanoid' game. It is based on Atari Breakout. A member of my population contains a string of 0's and 1's.(Population ...
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1answer
351 views

Genetic Algorithm - creatures in 2d world are not learning

Goal - I am trying to implement a genetic algorithm to optimise the fitness of a species of creatures in a simulated two-dimensional world. The world contains edible foods, placed at random, and a ...