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).

Filter by
Sorted by
Tagged with
1
vote
2answers
32 views

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 ...
2
votes
1answer
36 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 ...
0
votes
1answer
104 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 a to create genes representing these tasks in different orders. ...
4
votes
1answer
33 views

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 ...
1
vote
0answers
45 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 ...
1
vote
1answer
31 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 ...
4
votes
2answers
69 views

What is the difference between genetic algorithms and evolutionary game theory algorithms?

What is the difference between genetic algorithms and evolutionary game theory algorithms?
0
votes
1answer
27 views

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 ...
1
vote
0answers
36 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 ...
2
votes
1answer
26 views

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 ...
1
vote
1answer
82 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 ...
6
votes
1answer
156 views

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 ...
4
votes
1answer
50 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 ...
2
votes
0answers
22 views

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 ...
5
votes
0answers
42 views

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=...
2
votes
1answer
35 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 ...
1
vote
0answers
44 views

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 ...
0
votes
1answer
69 views

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: ...
1
vote
0answers
39 views

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 ...
2
votes
0answers
47 views

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 ...
4
votes
2answers
208 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-...
2
votes
1answer
49 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 ...
2
votes
1answer
67 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 ...
4
votes
1answer
52 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 ...
0
votes
0answers
80 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 ...
1
vote
0answers
30 views

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 ...
1
vote
1answer
76 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?
2
votes
1answer
302 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 ...
4
votes
2answers
348 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 ...
3
votes
1answer
93 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, ...) ...
3
votes
0answers
17 views

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 ...
1
vote
1answer
72 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 ...
1
vote
1answer
59 views

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.
2
votes
0answers
12 views

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 ...
1
vote
0answers
64 views

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 ...
1
vote
1answer
50 views

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 ...
1
vote
0answers
33 views

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 ?
1
vote
2answers
54 views

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 ...
3
votes
2answers
138 views

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. ...
3
votes
1answer
66 views

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 (...
2
votes
2answers
309 views

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....
1
vote
1answer
103 views

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!
3
votes
2answers
90 views

Why do we apply the mutation operation after generating the offspring?

Why do we apply the mutation operation after generating the offspring, in genetic algorithms?
3
votes
1answer
476 views

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 ...
1
vote
2answers
1k 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 ...
6
votes
3answers
887 views

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 ...
2
votes
1answer
64 views

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, ...
1
vote
1answer
124 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 ...
4
votes
4answers
2k views

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?
4
votes
4answers
217 views

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,...