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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How to avoid running out of solutions in genetic algorithm due to selection?

The genetic algorithm consists of 5 phases of which 4 are repeated: Initial population (initially) Fitness function Selection Crossover Mutation In the selection phase, the number of solutions ...
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ALL OUTPUTS for my neural network return SAME as [0.0, 0.0, 0.0] all of time. Trying to make an AI that plays the Snake Game in Python using NEAT

I am trying to make an AI that plays the Snake Game using the NEAT library in Python. I have most things figured out. I have chosen 6 inputs for my neural network -> Is it clear in forward ...
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What is meant by gene, chromosome, population in genetic algorithm in terms of feature selection?

I am trying to understand the genetic algorithm in terms of feature selection and these features are extracted using a machine learning algorithm. Let's suppose I have data of heart rate for 3 minutes ...
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Crossover method for gene value containing a set of values

I have a chromosome where each gene contain s set of values. Like the following: chromosome = [[A,B,C],[C,B,A],[C,D,],[],[E,F]] The order in each gene values matters. (A,B,C is different to A,C,B) ...
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How to effectively crossover mathematical curves?

I'm trying to optimize some reflective properties of curves of the form: $a_1x^n+a_2x^{n-1}+a_3x^{n-2} + ... + a_n + b_1y^n+b_2y^{n-1}+b_3y^{n-2} + ... + b_n = 0$ which is basically the curve that ...
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1answer
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How do I determine the genomes to use for crossover in NEAT?

If I have the fitness of each genome, how do I determine which genome will crossover with which, and so on, so that I get a new population? Unfortunately, I can't find anything about it in the ...
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1answer
39 views

How does the crossover operator work when my output contains only 2 states?

I'm currently working on a project where I am using a basic cellular automata and a genetic algorithm to create dungeon-like maps. Currently, I'm having an incredibly hard time understanding how ...
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Genetic Algorithm Python Snake not improving

So, i have created Snake game using Pygame and Python. Then i wanted to create an AI with Genetic algorithm and a simple NN to play it. Seems pretty fun, but things aren't working out. This is my ...
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What does it mean if classification error is equal between two networks but the MSE is different?

I'm experimenting with training a feedforward neural network using a genetic algorithm and I've done a few tests using both the mean squared error and classification error functions as fitness ...
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How to perform classification with NEAT-Python?

I am trying to do classification using NEAT-python for the first time, and I am having difficulty getting the accuracy rate. I tried the same problem with an ANN and was able to get a good accuracy ...
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1answer
64 views

What is the difference between evolutionary computation and evolutionary algorithms?

A book on evolutionary computation by De Jong mentions both the term evolutionary algorithms (EA) as well as evolutionary computation (EC). However, it remains unclear to me what the difference ...
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Using ML for Enemy Generation in Video Games

I am attempting to make a 2-D platformer game where the player traverses through an evil factory that is producing killer robots. The robots spawn at multiple specific locations in each level and ...
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Are connections genes in a genome ever deleted or just disabled?

When a new node is added, the previous connection is disabled and not removed. Is there any situation in which a connection gene is removed? For example, in the above diagram connection gene with ...
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1answer
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How does crossover work in a genetic algorithm?

If I had the weights of a certain number of "parents" that I wanted to crossbreed, and I used whatever method to pick out the "best parents" (I used a roulette wheel option, if that's any relevant), ...
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In machine learning, how can we overcome the restrictive nature of conjunctive space?

In machine learning, problem space can be represented through concept space, instance space version space and hypothesis space. These problem spaces used the conjunctive space and are very restrictive ...
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1answer
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What are evolutionary algorithms for topology and weights evolving of ANN (TWEANN) other than NEAT?

I wonder, if there are other than NEAT approaches to evolving architectures and weights of artificial neural networks? To be more specific: I am looking for projects/frameworks/libraries that use ...
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Intelligent crossover for binary chromosomes

I'm studying about genetic algorithm. I'm studying about different crossover operations used for binary chromosomes. These methods usually don't use any intelligence (1-point crossover, uniform ...
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1answer
45 views

How can I develop a genetic algorithm with a constraint on the sum of alleles?

I'm working on a genetic algorithm with a constraint on the sum of the alleles, e.g. if we use regular binary coding and a chromosome is 5-bits long I'd like to constrain it so that the sum of the ...
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2answers
116 views

How can I input tasks in a genetic algorithm with three different orders?

How can I structure my genetic algorithm to output ordered arrays? I have some tasks, let's call them $\{1,2,3,4,5\}$ and I would like to create genes representing these tasks in different orders. ...
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1answer
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Are there any strategies that would help me visualize the 'behavior space' and make a novelty function?

In “Abandoning Objectives: Evolution through the Search for Novelty Alone”, it is explained how the novelty search is a function that is domain specific, depending on the differing behaviors that can ...
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51 views

Reinforcement learning for a 2D game involving two players

I'd like to create an AI for a 2D game involving two players fighting against each other. The map look something like this (The map is a NxN array somehow randomly generated): Basically the players ...
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1answer
48 views

How are weights updated in a genetic algorithm with neural network?

Suppose an AI is to play the game flappy bird. And the fitness function is how long the bird has traveled before the game ends. Would we have multiple neural networks initialized at the beginning ...
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What is the difference between genetic algorithms and evolutionary game theory algorithms?

What is the difference between genetic algorithms and evolutionary game theory algorithms?
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1answer
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Training methods for bipedal robot

I am looking to train a bipedal robot using unity as a scape with a genetic algorithm. I will import the CAD into unity so the hardware is exact. My questions: Is Unity physics accurate enough to ...
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1answer
60 views

Unable to achieve expected outputs using NEAT for the 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 ...
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1answer
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The disadvantage of maximum number of fitness function call as stop criteria

I'm studying different stop criteria in genetic algorithm and advantages and disadvantages of each of them for evaluating different algorithms. One of these methods is max number of fitness function ...
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1answer
86 views

An “elevator pitch” breakdown of areas of applications for Reinforcement Learning & Neural Networks vs. Genetic Algorithms

I'm looking for an "elevator pitch" breakdown of areas of applications for Reinforcement Learning & Neural Networks vs. Genetic Algorithms, both actual and theoretical. Links are welcome, but ...
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Distance between pointers in Stochastic Universal Sampling (SUS)

I'm studying about different selection methods in genetic algorithm. My question is about Stochastic Universal Sampling (SUS) selection method. I know that each individual will occupy a segment of the ...
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1answer
60 views

What are examples of optimization problems that can be solved using a genetic algorithm?

I'm trying to learn how a genetic algorithm can solve optimization problems. I have already learned how a genetic algorithm can solve knapsack, TSP and set cover problems. I'm looking for some other ...
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1answer
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How to calculate multiobjective optimization cost for ordinary problems?

What I did: Created a population of 2D legged robots in a simulated environment. Found the best motor rotation values to make the robots move rightward, using an objective function with Differential ...
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Question about minimizing sum of remainders

I have a set of integers [$c_1$, $c_2$, $c_3$, ... , $c_N$]. A non-negative integer D, greater than a certain threshold, divides each 𝑐𝑖 and leaves remainder 𝑟𝑖,i.e., $r_i$ can be written as $r_i=...
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1answer
40 views

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
332 views

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
79 views

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
74 views

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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1answer
63 views

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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139 views

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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1answer
86 views

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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1answer
306 views

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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452 views

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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1answer
135 views

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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1answer
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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 ...