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.

Filter by
Sorted by
Tagged with
1
vote
0answers
115 views

If it evolves to perform many missions, won't it become a universal intelligence? [closed]

The more problems an agent can solve, the higher the probability of natural selection. Isn't this the process by which humans have become general-purpose intelligence by solving many problems in ...
4
votes
1answer
36 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 ...
1
vote
0answers
77 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 ...
0
votes
1answer
17 views

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 ...
0
votes
1answer
44 views

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 ...
2
votes
1answer
39 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 ...
0
votes
1answer
58 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/...
1
vote
1answer
21 views

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 ...
1
vote
0answers
18 views

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 \...
-1
votes
1answer
29 views

Is a neural network an evolutionary algorithm? [closed]

Is a neural network not just an evolutionary algorithm with increased amount of parameters to represent, and optimize a problem in the world?
0
votes
0answers
9 views

Is Universal Sentence Encoder helping producing supervised or not summaries?

I am currently working on generating automatic summaries of scientific texts and am wondering whether using Google's Universal Sentence Encoder makes my approach data-driven or supervised. I am doing ...
1
vote
1answer
53 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 ...
3
votes
1answer
56 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 ...
2
votes
1answer
188 views

What is the difference between a fitness function and a reward function?

In reinforcement learning (RL), the reward function (RF), which can be denoted as $r(s)$, $r(s, a)$, $r(s, a, s')$, $r(s, s')$ depending on its specific definition, provides the learning signal, which ...
0
votes
0answers
17 views

Neuroevolution + RL: How to make sure my policies are more diverse?

I currently implemented Deep Neuroevolution and used it on a couple of Atari games. For my implementation I used a similar Genetic Algorithm, network and setup as the Uber AI Deep Neuroevolution paper ...
0
votes
1answer
70 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 ...
1
vote
1answer
40 views

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 ...
0
votes
1answer
78 views

Isn't evolutionary theory the essence of intelligence after all?

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 ...
0
votes
0answers
27 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 ...
0
votes
1answer
69 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 ...
1
vote
1answer
36 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 ...
0
votes
0answers
34 views

How are the step size and covariance matrix updated in CMA-ES?

I've been following the tutorial The CMA Evolution Strategy: A Tutorial to try and understand the CMA-ES, but I'm having trouble understanding how the step size and the covariance matrix are been ...
2
votes
0answers
73 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 ...
2
votes
0answers
37 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 ...
1
vote
2answers
235 views

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 ...
1
vote
0answers
27 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) ...
8
votes
1answer
838 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 ...
1
vote
0answers
32 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 ...
2
votes
0answers
178 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 ...
4
votes
1answer
76 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 ...
2
votes
1answer
138 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 ...
1
vote
2answers
61 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 ...
4
votes
1answer
48 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 ...
4
votes
2answers
143 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?
2
votes
0answers
54 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 ...
2
votes
3answers
242 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 ...
5
votes
1answer
238 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 ...
2
votes
1answer
55 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
1answer
143 views

Why evolutionary training of neural networks is not popular?

Evolutionary algorithms are mentioned in some sources as a method to train a neural network (finding weights, not hyperparameters). However, I have not heard about one practical application of such an ...
3
votes
1answer
47 views

Why do all nodes in a GP tree need to be the same type?

Context: I'm a complete beginner to evolutionary algorithms and genetic algorithms and programming. I'm currently taking a course about genetic algorithms and genetic programming. One of the concepts ...
4
votes
0answers
86 views

Why isn't the evolutionary Turing machine mainstream?

Given that recurrent neural networks are equivalent to a Turing machine, then why isn't the evolutionary Turing machine, e.g. described in the paper Evolution of evolution: Self-constructing ...
1
vote
0answers
25 views

Is there a rule-of-thumb to determine which behaviours must be learned in a lifetime and which innate?

I was training an AI to learn things during its lifetime such as find food and navigate a maze. Behaviors that might change during its lifetime. But I hit upon a snag. Some behaviors, like avoiding ...
1
vote
0answers
42 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
1answer
85 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 ...
2
votes
1answer
446 views

Is there any research work that attempts to combine neuroevolution with deep reinforcement learning?

Neuroevolution can be used to evolve a network's architecture (and weights, of course). Deep reinforcement learning, on the other hand, has been proven to be extremely powerful at optimising the ...
1
vote
0answers
233 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
32 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 ...
2
votes
1answer
321 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 ...
2
votes
2answers
137 views

How to reduce amount of species in NEAT?

I am using the following library: https://github.com/vishnugh/evo-NEAT which seems to be a pretty simple NEAT-implementation. Therefore I am using the following Config: ...
0
votes
0answers
51 views

How do I choose an appropriate fitness function and hyper-parameters to train a 7-DOF arm?

I am trying to train an ANN to control a 7 Degrees-Of-Freedom arm. It should reach a target avoiding a single obstacle. Given my modeling of the situation, my input layer is composed of 12 nodes: 5 ...