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Questions tagged [evolutionary-algorithms]

For questions about evolutionary algorithms (EAs), which use mechanisms inspired by biological evolution, such as mutation, recombination, and/or selection. EAs comprise genetic algorithms (GAs), genetic programming (GP), evolution strategies (ES), neuroevolution (NE), and so on. EAs are a sub-field of evolutionary computation, which comprises also ant colony optimization or particle swarm optimization, among others.

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Creating a replacement for backpropagation through evolution [closed]

Can we create a learning algorithm that solves all the problems of backpropagation through evolution?
Display name's user avatar
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What's the overall algorithm for population evolution in the NEAT algorithm?

I am implementing NEAT from scratch using Ruby, and I'm having a hard time understanding the necessary steps and overall algorithm of what happens between generations. I have the ...
Thiago Belem's user avatar
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1 answer
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Equivalent of symbolic regression but for code instead of math expression

I'm already well versed with Genetic/Memetic algorithms and similar algorithms. I know about Symbolic regression, where some dataset is fitted through a math expression evolution, but I'm wondering, ...
Nordine Lotfi's user avatar
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1 answer
28 views

Navigating encoder-only text/sentence embedding models

tldr; I am researching/looking for vec2text methods that work (a) without training a special model to guide the mutations, and (b) without access to the model weights. I am doing some experiments in ...
Realz Slaw's user avatar
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0 answers
8 views

Algorithm Suggestion for Diverging Data (Severity/Intensity Analysis)

I have four datasets for four different accidents; each dataset has the same parameters. Some of the key parameters are changing their values from a "standard value". The more they change ...
Rubayet Alam's user avatar
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Less mutation rate is performing better in bigger neural network

I have a genetic AI neural network that evolves every generation and can add or remove neurons and change weights. It evolves good in first generations with mutation rate probability of e.g. ...
Mahdyfo's user avatar
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1 answer
198 views

Is evolutionary algorithm dead as same as symbolic AI?

I am just wondering if evolutionary algorithm (e.g., genetic algorithm, ant colony optimization, swarm optimization, etc.) dead as same as symbolic AI. Can you give me the latest situation as of June ...
user366312's user avatar
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Longer DNN training times when using evolutionary algorithms

I am comparing my deep neural network (DNN) performance when using 2 types of optimizers: gradient-based Adam (properly tuned) and a population-based optimization algorithm (e.g., genetic algorithm (...
knowledge_seeker's user avatar
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1 answer
173 views

Crossover and Mutation function for value encoding [closed]

I have been trying to attempt writing a Genetic Algorithm using value encoding (fixed-length vectors of real numbers) instead of binary encoding. So far the code I have written works, but needs quite ...
No_Name's user avatar
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2 answers
397 views

Do genetic algorithms "learn"?

I am currently working my way into Genetic Algorithms (GA). I think I have understood the basic principles. I wonder if the time a GA takes to go through the iterations to determine the fittest ...
user avatar
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0 answers
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How do I use the N correctly in NEATs speciation delta function?

When implementing NEAT I'm having some issues with the speciation distance/delta function, specifically the term N (number of genes in biggest genome). Won't term $N$ in $δ=c1*E/N+c2*D/N+c3*W$ just ...
egil87's user avatar
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Does the policy search work if there is no state to state dependency through actions?

There is a game in which the state comes one after the other without depending on the agent's action. The agent gets a reward for its actions at the end of the game. The goal of the agent is to reach ...
veerendra's user avatar
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1 answer
215 views

How does OpenAI-ES use Adam?

I just read that OpenAI's ES uses Adam: "OpenAI’s ES is denoted as “OptimES” (since it uses Adam optimizer)"?? I verified they are correct using the link they posted, (see es_distributed/...
profPlum's user avatar
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How to represent multiple-output logic circuits in tree-based genetic programming

Consider the following digital logic circuit, which has multiple inputs and one output: The logic circuit above can be represented in tree form: This tree representation could then be used in a tree-...
Flux's user avatar
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neat - what is the purpose of looped networks?

So im writing my own implementation of NEAT and i'm wondering how looped networks (like one shown in the image) can be useful. I'll probably implement them anyway because i want to fiddle around with ...
xfed's user avatar
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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 ...
Joseph Walker's user avatar
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1 answer
174 views

Is there a benchmark for multi-objective evolutionary algorithms?

I'm working on a project for an evolutionary algorithms course, and the problem we're trying to solve is multi-objective. We'll use NSGA-II but we also wanted to compare with some other MOEAs, however,...
Matías Santurio's user avatar
3 votes
1 answer
171 views

What does "unknown search spaces" mean in the context of Evolutionary Algorithms?

In the article Multi-Verse Optimizer: a nature-inspired algorithm for global optimization (DOI 10.1007/s00521-015-1870-7), it's written The results of the real case studies also demonstrate the ...
Commander's user avatar
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5 votes
1 answer
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When would you use Evolutionary Strategies over Step-Based Reinforcement Learning

In Salimans et al, 2016, the authors argue that ES should be considered a competitive alternative to MDP-based RL algorithms like Q-Learning, TRPO. However, in practice, I notice that more often than ...
ganto's user avatar
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4 votes
1 answer
332 views

Does elitism cause premature convergence in genetic algorithms?

I have a genetic algorithm which is working fairly well. It's got all the standard operators, including initial random population, crossover ratio, mutation rate, degree of mutation, etc. This works ...
Pittsburgh DBA's user avatar
1 vote
0 answers
120 views

What is the difference between ERL and EA by considering it as RL?

I am currently studying as an MSCS student and my research is based on Evolutionary Algorithm as Reinforcement Learning, and I am confused about the following terms: What is the difference between ...
Tibu's user avatar
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1 answer
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What approach would work well for predicting earthquake intensity based on historical data?

My problem: I own warning system where I collect data from institutions and send them over through various ways to users. I would like to hear your advice on what approach I can use for solving my ...
Banik's user avatar
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1 answer
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Is there a name for this approach to evolutionary algorithms?

I am considering an approach to evolutionary algorithms, in which instead of maintaining a population of individuals, we maintain a pool of $N$ mutations that can be applied to a base genome. For ...
causative's user avatar
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3 votes
1 answer
390 views

What is the most computationally efficient genetic algorithm?

In researching genetic algorithms, it seems that there are various methods of selection and other operator methods that can significantly change the performance. For example, this picture contains ...
Ron Germano's user avatar
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1 answer
67 views

Does a differential evolution algorithm mutate its population during a generation?

I'm implementing a differential evolution algorithm and when it comes to evolving a population, the page I am referencing is vague on how the new population is generated. https://en.wikipedia.org/wiki/...
gator's user avatar
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1 answer
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How to handle equality constraints in the mutation operation of evolutionary algorithms?

I am new in evolutionary algorithms field. I have a chromosome of 6 variables (real variable), where the sum of these variables is equal to 1. I am looking for mutation formulas that can generate a ...
Rahim Brahimi's user avatar
1 vote
0 answers
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Clonal operator in Immune Clonal Strategy

I was reading about Immune Clonal Strategy, specifically about Monoclonal operator from Immunity clonal strategies, and it goes as follows: Here $a_i $ is a point and $a_i = \{ x_1, x_2, \cdots, x_m \...
Kais Hasan's user avatar
1 vote
1 answer
624 views

How to deal with evolutionary/genetic fitness function that can have both negative and positive values?

I am optimising function that can have both positive and negative values in pretty much unknown ranges, might be -100, 30, 0.001, or 4000, or -0.4 and I wonder how I can transform these results so I ...
GKozinski's user avatar
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3 votes
1 answer
238 views

Are Genetic Algorithms suitable for problems like the Knuth problem?

We all know that Genetic Algorithms can give an optimal or near-optimal solution. So, in some problems like NP-hard ones, with a trade-off between time and optimal solution the near-optimal solution ...
yaminoyuki's user avatar
-1 votes
1 answer
176 views

What is a codon in grammatical evolution?

The term codon is used in the context of grammatical evolution (GE), sometimes, without being explicitly defined. For example, it is used in this paper, which introduces and describes PonyGE 2, a ...
nbro's user avatar
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1 vote
1 answer
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What is the difference between sensitivity analysis and parameter tuning?

I tried different values of genetic algorithm operators: many crossover rates from 20% to 80% many crossover rates from 1% to 20% varying the population size The study of different parameter values ...
fathese's user avatar
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1 answer
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Isn't evolutionary theory the essence of intelligence after all? [closed]

The theory of evolution seems to be intelligent as it creates life The mechanism of evolutionary theory consists of mutation, recombination, and natural selection like a genetic algorithm. Isn't this ...
Dimer's user avatar
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0 answers
32 views

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 ...
mponagandla's user avatar
0 votes
1 answer
205 views

What are trap functions in genetic algorithms? [duplicate]

What are trap functions in genetic algorithms? Suppose you ran a GA with a trap function and examined the population midway through the run. Can someone explain what you would expect the population to ...
Re-coder08's user avatar
1 vote
1 answer
94 views

Choosing an AI method to recreate a given binary 2D image

If the title wan not very clear, I want a method to take an input image like this, [[0, 0, 0, 0], [1, 1, 1, 0], [1, 1, 1, 0], [0, 1, 1, 0]] and output the 2D ...
doca's user avatar
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4 votes
1 answer
336 views

NEAT can't solve XOR completely

I'm currently implementing the NEAT algorithm. But problems occur when testing it with problems which don't have a linear solution(for example xor). My xor only produces 3 correct outputs once at a ...
Creepsy's user avatar
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3 votes
0 answers
131 views

Artificial life simulator that is fully embodied and passes open endedness tests

Geb is an alife simulation that as far as I know passes all of the tests we have tried to come up with in defining open endedness. However, when you actually run the code, the behavioral complexity ...
Phylliida's user avatar
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1 vote
2 answers
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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 ...
Talha Anwar's user avatar
1 vote
0 answers
34 views

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) ...
Carol's user avatar
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10 votes
1 answer
3k views

What is the difference between reinforcement learning and evolutionary algorithms?

What is the difference between reinforcement learning (RL) and evolutionary algorithms (EA)? I am trying to understand the basics of RL, but I do not yet have practical experience with RL. I know ...
Single Malt's user avatar
1 vote
0 answers
40 views

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 ...
jan's user avatar
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2 votes
0 answers
685 views

How to select good inputs and fitness function to achive good results with NEAT for Icy Tower bot

I'm trying to make a bot to the famous "Icy Tower" game. I rebuilt the game using pygame and I'm trying to build the bot using Python-NEAT. Every generation a population of 70 characters ...
Lidor shimoni's user avatar
5 votes
1 answer
506 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 ...
dan888's user avatar
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3 votes
1 answer
711 views

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 ...
GKozinski's user avatar
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1 vote
2 answers
194 views

Are there clever (fitness-based) crossover operators for binary chromosomes?

While studying genetic algorithms, I've come across different crossover operations used for binary chromosomes, such as the 1-point crossover, the uniform crossover, etc. These methods usually don't ...
Pablo's user avatar
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4 votes
1 answer
73 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 ...
DoubleDouble's user avatar
4 votes
2 answers
429 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?
DRV's user avatar
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2 votes
0 answers
119 views

What is the difference between evolutionary game theory and meta-heuristics?

Here is a list of meta-heuristic algorithms Ant colony optimization, Ant lion optimizer, Artificial bee colony algorithm, Bat algorithm, Cat swarm optimization, Crow search algorithm, Cuckoo ...
DRV's user avatar
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2 votes
3 answers
336 views

What is the name of an AI whose primary goal is to create a better AI?

A general AI x creates another AI y which is better than x. y creates an AI better than itself. And so on, with each generation's primary goal to create a better AI. Is there a name for this. By ...
Ashwin Rohit's user avatar
5 votes
1 answer
2k views

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

I'm trying to learn how genetic algorithms can solve optimization problems. I have already learned how genetic algorithms can solve the knapsack, TSP and set cover problems. I'm looking for some other ...
Pablo's user avatar
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