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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14
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5answers
4k views

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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2answers
361 views

How should I encode the structure of a neural network into a genome?

For a deterministic problem space, I need to find a neural network with the optimal node and link structure. I want to use a genetic algorithm to simulate many neural networks to find the best network ...
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2answers
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How does “novelty search” work?

The author claims that guiding evolution by novelty alone (without explicit goals) can solve problems even better than using explicit goals. In other words, using a novelty measure as a fitness ...
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5answers
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Is a genetic algorithm an example of artificial intelligence?

Since human intelligence presumably is a function of a natural genetic algorithm in nature, is using a genetic algorithm in a computer an example of artificial intelligence? If not, how do they differ?...
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4answers
228 views

Spontaneous emergence of replicators in Artificial Life

One of the corner stones 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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6answers
543 views

Open-source tool for home AI learning/experimentation?

I'd like to do some experimenting with neural net evolution (NEAT). I wrote some GA and neural net code in C++ back in the 90s just to play around with, but the DIY approach proved to be labor-...
9
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1answer
944 views

Neural networks vs Genetic algorithms in games like Tic Tac Toe?

Currently I'm doing a project that's about creating an AI to play the game Gomoku (It's like tic tac toe, but played on a 15*15 board and requires 5 in a row to win). I have already successfully ...
8
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3answers
233 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 ...
8
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1answer
210 views

Are there any other machine learning models apart from Reinforcement Learning and Q Learning to play video games?

OpenAI's Universe utilises RL algorithms and I have heard of some game-training projects using Q learning, but are there any others which are used to master/win games? Can genetic algorithms be used ...
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445 views

Artificial Life - life or not?

I define Artificial Life as a "simulation" or "copy" of life. However, should it be considered a simulation or copy? If one had motivation and money, someone could theoretically create evolving ...
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2answers
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What is a Markov chain and how can it be used in creating artificial intelligence?

I believe a Markov chain is a sequence of events where each subsequent event depends probabilistically on the current event. What are examples of the application of a Markov chain and can it be used ...
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2answers
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Mutation and crossover in a genetic algorithm with real numbers

How exactly are "mutation" and "cross-over" applied in the context of a genetic algorithm based on real numbers (as opposed to just bits)? I think I understood how those two phases are applied in a "...
6
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1answer
249 views

How does mating take place in NEAT?

In the Evolving Neural Networks through Augmenting Topologies (NEAT) paper it says (p. 110): The entire population is then replaced by the offspring of the remaining organisms in each species. ...
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1answer
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What is the difference between Memetic Algorithms and Genetic Algorithms?

Can someone please explain the difference between Memetic Algorithms and Genetic Algorithms? Is an indivudal's lifetime learning part of memetic algorithms?
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3answers
567 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 ...
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3answers
332 views

Could GA's determine fitness by “Fighting” against each other?

I am developing AI in the form of NEAT, and it has passed certain tasks like the XOR problem outlined in the NEAT Research Paper. In the XOR Problem, the fitness of a network was determined by an ...
5
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1answer
692 views

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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2answers
587 views

Does NEAT require only connection genes to be marked with a global innovation number?

Does NEAT require only connection genes to be marked with a global innovation number? From the NEAT paper Whenever a new gene appears (through structural mutation), a global innovation number is ...
5
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2answers
1k views

Is it possible to classify data using a genetic algorithm?

Is it possible to classify data using a genetic algorithm? For example, would it be possible to sort this database? Any example in Matlab?
5
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1answer
606 views

When do mutations in NEAT occur?

I read through the Evolving Neural Networks through Augmenting Topologies (NEAT) paper. I understand the algorithm now, but one thing is still unclear to me. When does the mutation occur and how ...
5
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1answer
195 views

Advice on machine learning for a neural network

I'm aiming to create a neural network that can learn to predict the next state of a board using the rules of Conway's Game of Life. This is technically three questions, but I felt that they needed to ...
5
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1answer
485 views

What happens if 2 genes have the same connection but a different innovation number?

I have read the Evolving Neural Networks through Augmenting Topologies (NEAT) paper, but some doubts are still bugging me, so I have two questions. When do mutations occur? Between which nodes? When ...
5
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3answers
868 views

What is an appropriate fitness function for a simulated self-driving car?

I have been working for ages on a neuro-evolution AI program, where cars learn how to race around a track. Presently, I have a rudimentary fitness function that awards points for every degree ...
5
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1answer
472 views

Is there an efficient way to implement a random crossover of individuals stored in a matrix?

I am using a GA to optimise an ANN in Matlab. This ANN is pretty basic (input, hidden, output) but the input size is quite large (10,000) and the output size is 2 since I have to classes of images to ...
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0answers
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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=...
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2answers
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What genetic algorithm designs are there that includes models of epigenetics?

What designs for genetic algorithms are there, if they are classified differently and/or have different names, that leverage models for epigenetics in evolution? What are the pros/cons of the designs? ...
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4answers
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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?
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1answer
443 views

NEAT crossover - what to do with disjoint and excess genes

According to the original paper "Genes that do not match are inherited from the more fit parent" But what if the more fit parent has lesser nodes compared to the other, will the disjoint/excess genes ...
4
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2answers
162 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-...
4
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1answer
73 views

Summed weights are too big for activation function [GANN]

I am trying to create a fixed-topology MLP network from scratch (C#) which can classify some simple problems such as XOR and MNIST (Handwriting). The network will be trained purely with genetic ...
4
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1answer
2k views

Several questions regarding the NEAT algorithm

I've recently read the paper Evolving Neural Networks through Augmenting Topologies which introduces NEAT. I am now trying to prototype it myself in JavaScript. However, I stumbled across a few ...
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4answers
138 views

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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4answers
195 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,...
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1answer
44 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 ...
4
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1answer
225 views

Fitness Function altenatives in Genetic Algorithms for game AI

I have created a Gomoku(5 in a row) AI using Alpha-Beta Pruning. It makes moves on a not-so-stupid level. First, let me vaguely describe the grading function of the Alpha-Beta algorithm. When it ...
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0answers
175 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 ...
4
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1answer
1k views

Genetic Algorithm: Is Elitism prefered in cross-over operator?

There are two potential approaches when performing cross-over operation in genetic algorithm: perform cross-over on Elites in the pool, probably the ones that are also going to be directly transfered ...
4
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1answer
727 views

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 ...
3
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3answers
732 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?
3
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1answer
55 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
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1answer
530 views

how to represent the weights of a neural network as binary strings for 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 ...
3
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1answer
67 views

Genetic Algorithms: Trade-off between time and variance with regards to fitness function

I'm developing an AI to play a card game with a genetic algorithm. Initially, I will evaluate it against a player that plays randomly, so there will naturally be a lot of variance in the results. I ...
3
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1answer
353 views

Genetic Algorithm - creatures in 2d world are not learning

Goal - I am trying to implement a genetic algorithm to optimise the fitness of a species of creatures in a simulated two-dimensional world. The world contains edible foods, placed at random, and a ...
3
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2answers
113 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
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1answer
60 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 (...
3
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1answer
375 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 ...
2
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3answers
117 views

Do genetic algorithm and neural networks really think?

I'm aware of those AI programmes which can play games and neural networks which can identify pictures. But are they really thinking. Do they think like humans? Do they have consciousness? Or are they ...
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3answers
228 views

Do intelligent systems make mistakes?

The intelligence of the human brain is said to be a strong factor leading to human survival. The human brain functions as overseer for many functions the organism requires. Like that, the most ...
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2answers
286 views

What's the difference in between biological evolution and artificial evolution?

I am trying to understand the difference between the workings biological evolution and artificial evolution. If we look at it in terms of genetics, in both of them, selection is the key term, natural ...
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2answers
221 views

NEAT - Can mutation enable a disabled connection?

In the add node mutation, the connection between two chosen nodes (e.g A and B) is first disabled and then a new node is created between A and B with their respective two connections. I guess that the ...