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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Are Genetic Algorithms suitable for a problem with a non-unique optimal solution?

I was wondering if a genetic algorithm is useful if the optimization problem has several optimal solutions. My thought was that I should not use it since when combining two members of a population who ...
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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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4 votes
1 answer
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Traveling salesman problem variant: which algorithm to choose?

I have an industrial problem which I'm trying to cast as a Traveling Salesman problem (TSP) in 3D euclidian space. There are physical limitations which implies that some subpaths may or may not be ...
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3 votes
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How does the paper implement NEAT without a global set tracking Innovations?

I have been reading this paper on NEAT and trying to implement the algorithm in C#. For the most part, I understand everything in the paper however, there are 2 things I don't understand that confuse ...
3 votes
0 answers
50 views

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 ...
3 votes
0 answers
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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 ...
3 votes
2 answers
814 views

NEAT - Managing species across generations

I (mis?)understood the NEAT algorithm has the following steps: Create a genome pool with N random genomes Calculate each genome fitness Assign each genome to a species Calculate the adjusted fitness ...
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3 votes
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Is there a measure of AI relative strength, modified by resources?

For instance, Strength/Size$\times$Speed, where size and speed refer to memory and processing. We now have very strong, narrow AI, but they tend to run on fast hardware without volume restrictions. To ...
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2 votes
1 answer
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How to decode P bits that represent a random weight generator?

So I've been tasked by my neural network professor at university to replicate the following research: Intelligent Breast Cancer Diagnosis Using Hybrid GA-ANN. Each chromosome represents a possible net,...
2 votes
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100 views

In NEAT, how do node numbers work?

I have read a lot of debates about node ids and such. I'm not 100% sure how it works, but I am assuming the next node added to a network would be the next number in that specific networks list? For ...
2 votes
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79 views

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 ...
2 votes
1 answer
160 views

Is there any disadvantage of the maximum number of fitness function call as a stop criterion?

I'm studying different stop criteria in genetic algorithms and the advantages and disadvantages of each of them for evaluating different algorithms. One of these methods is the max number of fitness ...
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2 votes
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121 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 ...
2 votes
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57 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 ...
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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 ...
2 votes
0 answers
208 views

Is it possible to learn to estimate the minimum value in a table?

Is it possible to classify or learn to estimate the minimum value in a table if the values are integer and represented 32 bits (and we can input all variables at the same moment, like in system on a ...
1 vote
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32 views

Is there anything remotely as successful as backprop, but for training programs, not neural networks?

Backprop is used to train deep neural networks to remarkable success. Deep neural networks, on the other hands, can be seen as as a specific kind of computer function that receives inputs and produces ...
1 vote
0 answers
126 views

How to calculate adjusted and normalized fitness when a higher raw fitness is better

I am reading Genetic Programming: On the Programming of Computers by Means of Natural Selection by John R. Koza. For calculating the "standardized fitness" of an individual, where a lower ...
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1 vote
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170 views

Why does the schema theorem of genetic algorithms hold?

I have been reading about the Schema Theorem - one of the first theorems from the field of evolutionary computing and genetic algorithms, largely responsible for justifying the use of genetic ...
1 vote
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33 views

Would it be a good idea to mutate half of the offspring of each GA generation 100% of the time and the other half 0% of the time?

I was reading about genetic algorithms, and to my understanding a genetic algorithm (GA) is an algorithm that starts with an initial population of chromosomes, where each chromosome has associated ...
1 vote
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71 views

How should the 1-point crossover and mutation be defined for the problem of finding the largest circle that does not enclose any point?

For a random scattering of points, in a bounded area, the goal is to find the largest circle that can be drawn inside those same bounds that does not enclose any points. Solving this problem with a ...
1 vote
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43 views

If one of the inputs to a neural network (that represents a policy) is noisy and degrades the performance, would this architecture solve the issue?

I'm using genetic algorithms to train deep reinforcement learning (DRL) agents, similarly to what was done in this paper. DRL policies are therefore represented by deep neural networks, which map ...
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1 vote
1 answer
64 views

What are most commons methods to measure improvement rate in a meta-heuristic?

When I run a meta-heuristics, like a Genetic Algorithm or a Simulated Annealing, I want to have a termination criterion that stops the algorithms when there is not any significant fitness improvement. ...
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experiences on using genetic algorithms as a way to improve neural networks?

I wonder if there is research, patents, or libraries using Genetic algorithms (GA) to improve Neural Networks. I don't find anything in the subject. For example: use GA to find better parameters in a ...
1 vote
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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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1 vote
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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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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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503 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
0 answers
35 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 ...
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1 vote
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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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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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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 ...
1 vote
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Which algorithm would you use to solve a multiple producer-consumer problem with constraints?

I'm solving this problem similar to consumer-producer of materials (i.e. sand). This is the graph of the problem: Where Req (...
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Crossing complex and non uniform genomes?

I've been tinkering with an artificial life simulator, critterding for many years and lately ive been branching the project and adding fitness functions. Im still quiet new to genetic algorithms and ...
1 vote
2 answers
117 views

Where or for what could genetic algorithms be used in the context of project management?

Where or for what could genetic algorithms (GA) be used in the context of project management (PM)? I thought about task dispatching, but I'm looking for other potential uses of GAs in the context of ...
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21 views

How to evaluate a neural network that has recurrent connections

I was attempting to implement NEAT but I am facing a slight problem. how can I get the order for which to calculate the output of each neuron with recurrent connections present? I thought if a method ...
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28 views

Which of these 3 mutation rates is the best in terms of performance?

I am need some comments since I am conducting experiments with 3 different mutation rates and hesitate to choose the best one. I ...
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25 views

agent based DNN with a loopback

I have a data problem with no direct reward mechanism,(test/train) good and fault solutions. Though over a long time period good decisions might be made. I've been searching for days now for an agent ...
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How would you find the fitness function for the following puzzle?

A magic hexagon is a hexagon whose sum of each row and diagonal equals to a constant. I am currently searching a magic hexagon of order 3 with the magic constant = 38. I am using a genetic algorithm ...
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27 views

In NEAT, how do I prevent duplicate connections?

According to this paper, duplicate mutations are only given the same innovation numbers within the same generation. What do I do if a connection gets broken into 2 connections and a node during 2 ...
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141 views

How can I select features for a symbolic regression problem to be solved with genetic programming?

I want to solve a symbolic regression problem with genetic programming. My dataset is similar to this one, but I have 30 features, and I want to use only the most sensitive features. I found this ...
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Genetic algorithm stuck and cannot find an optimal solution

I'm working on SLAP (storage location assignment problem) using genetic algorithm implemented manually in the C++ programming language. The problem is fairly simple, we do have ...
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Unable to meet desired mean squared error

I wish to get MSE < 0.5 on test data (https://easyupload.io/zr7xf3) which is 20% of given data chosen randomly. But I am reaching 0.73 using both plain Ridge Regression as well as a neural network ...
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Which 6-bit string would represent an optimal solution for trap-3 in the Linkage Learning Genetic Algorithm?

I am struggling to learn certain Evolutionary algorithm concepts and also relations between each of them. I am going through the Linkage Learning Genetic Algorithm (LLGA) right now and came across ...