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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58 views

Why don't we try to mimic nature to build AI? [closed]

Humans are very complex biological machines. We don't solve very complicated formulas to find paths and don't store very high-dimensional data in our brains. Our intelligence and ability to think is ...
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289 views

Can NEAT produce neural networks where inputs are directly connected to outputs?

Can NEAT produce neural networks where inputs are directly (without intermediate hidden neurons) connected to outputs?
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307 views

Has the spontaneous emergence of replicators been modeled in Artificial Life?

One of the cornerstones of The Selfish Gene (Dawkins) is the spontaneous emergence of replicators, i.e. molecules capable of replicating themselves. Has this been modeled in silico in open-ended ...
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2k views

Does artificial intelligence write its own code?

Does artificial intelligence write its own code and then execute it? If so, does it create separate functions for each purpose?
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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 ...
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2answers
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Why does the fitness of my neural network to play tic-tac-toe keep oscillating?

I wrote a simple feed-forward neural network that plays tic-tac-toe: 9 neurons in input layers: 1 - my sign, -1 - opponent's sign, 0 - empty; 9 neurons in hidden layer: value calculated using ReLU; 9 ...
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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 ...
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1answer
41 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,...
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1answer
54 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 ...
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1answer
70 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 ...
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Evaluating species stagnation in NEAT

I'm exploring the NEAT algorithm, and among all of my questions on how to optimize my models, I was wondering how should I evaluate the stagnation of species in order to eventually extinct it. ...
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4answers
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Has the Fibonacci series or the golden ratio been applied in any way in AI?

I have been looking at the Fibonacci series, the golden ratio, and its uses in nature, like how flowers and animals grow based on the series. I was wondering whether we could use the Fibonacci series ...
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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 ...
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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 ...
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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 ...
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1answer
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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 ...
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1answer
19 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 ...
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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 ...
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1answer
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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 ...
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1answer
55 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 ...
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322 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 ...
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How can genetic programming be used for path planning?

I have been reading quite a few papers, on genetic programming and its applications, in particular, chapter 10 of "Genetic Programming: An Introduction and Tutorial, with a Survey of Techniques ...
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1answer
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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/...
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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 \...
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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 ...
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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 ...
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1answer
260 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 ...
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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 ...
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1answer
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How do I write a good evaluation function for a board game?

I'm currently writing the Alpha-Beta pruning algorithm for a board game. Now I need to come up with a good evaluation function. The game is a bit like snakes and ladders (you have to finish the race ...
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1answer
860 views

Does fitness proportionate selection select multiple individuals?

Does fitness proportionate selection select multiple individuals? So, I read on Wikipedia and on multiple Stack Exchange threads about fitness proportionate selection or rather roulette selection, but ...
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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 ...
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1answer
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How do I design a fitness function that weighs the importance of eating food?

Summary: I am teaching bots to pick food on a playing field. Some food is poisonous and some is good. Food Details: Poisonous food subtracts score points and good food adds. Food points vary based on ...
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1answer
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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 ...
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1answer
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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 ...
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3answers
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Is it possible to separately evolve a part of the population?

In a classic example of a genetic algorithm, you would have a population and a certain amount of simulation time to evaluate it and breeding. Then proceed to the next generation. Is it possible, ...
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1answer
245 views

Have evolutionary algorithms been used for engineering design?

Recently, I've been looking recently into what uses AI - specifically evolutionary algorithms - may have in automating engineering design. For a long time, there have been algorithms that solve ...
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495 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 ...
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What evolutionary algorithms are there that model epigenetics?

What evolutionary algorithms are there that model or incorporate some notion of epigenetics? What are the pros/cons of those approaches? Are there vast insufficiencies or wide-open questions about ...
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What exactly are genetic algorithms and what sort of problems are they good for?

I've noticed that a few questions on this site mention genetic algorithms and it made me realize that I don't really know much about those. I have heard the term before, but it's not something I've ...
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1answer
84 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 ...
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2answers
345 views

Do genetic algorithms also evolve?

After witnessing the rise of deep learning as automatic feature/pattern recognition over classic machine learning techniques, I had an insight that the more you automate at each level, the better the ...
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1answer
765 views

How to represent the weights of a neural network as binary strings for a genetic algorithm?

I want to train my neural network by evolution, that is I want to recombine the weights of the best performing neural networks in each evolution cycle or generation. My initial instinct was to ...
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How to evaluate a NEAT neural network?

I'm trying to write my own implementation of NEAT and I'm stuck on the network evaluate function, which calculates the output of the network. NEAT as you may know contains a group of neural networks ...
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2answers
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What is a trap function in the context of a genetic algorithm?

What is a trap function in the context of a genetic algorithm? How is it related to the concepts of local and global optima?
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1answer
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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 ...
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1answer
148 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, ...
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352 views

Why is cross-over a part of genetic algorithms?

Genetic Algorithms has come to my attention recently when trying to correct/improve computer opponents for turn-based strategy computer games. I implemented a simple Genetic Algorithm that didn't use ...
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2answers
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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 ...
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1answer
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Is elitism preferred over non-elitism in the cross-over operator?

There are two potential approaches when performing cross-over operation in genetic algorithms. Use only the elites in the pool, probably the ones that are also going to be directly transferred to the ...
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330 views

What are the available selection methods in genetic algorithms?

In a genetic algorithm, there are different steps. One of those steps is the selection of chromosomes for reproduction. What are the available selection strategies in genetic algorithms?