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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17
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5answers
5k 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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How does novelty search work?

In this article, 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 ...
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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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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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290 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
634 views

Open-source tools or libraries to experiment with neural networks and evolutionary algorithms [closed]

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-...
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3answers
325 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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Should I use neural networks or genetic algorithms to solve Gomoku?

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 1515 board and requires 5 in a row to win). I have already successfully ...
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1answer
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What is the difference between memetic algorithms and genetic algorithms?

What is the difference between memetic algorithms and genetic algorithms? Is an individual's lifetime a learning part of memetic algorithms?
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549 views

Is artificial life really 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 ...
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271 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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Given a list of integers $\{c_1, \dots, c_N \}$, how do I find an integer $D$ that minimizes the sum of remainders $\sum_i c_i \text{ mod } D$?

I have a set of fixed integers $S = \{c_1, \dots, c_N \}$. I want to find a single integer $D$, greater than a certain threshold $T$, i.e. $D > T \geq 0$, that divides each $c_i$ and leaves ...
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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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How do mutation and crossover work with real-valued chromosomes?

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 "...
7
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1answer
691 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 ...
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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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2answers
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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
184 views

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 ...
6
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2answers
504 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-...
6
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1answer
137 views

How to solve the problem of too big activations when using genetic algorithms to train neural networks?

I am trying to create a fixed-topology MLP from scratch (with C#), which can solve some simple problems, such as the XOR problem and MNIST classification. The network will be trained purely with ...
6
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1answer
383 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. ...
6
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1answer
412 views

How is the distance between pointers in Stochastic Universal Sampling determined?

I'm studying about different selection methods in genetic algorithms. My question is about the Stochastic Universal Sampling (SUS) selection method. I know that each individual will occupy a segment ...
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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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3answers
373 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 ...
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959 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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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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983 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 ...
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2answers
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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?
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336 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
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Several questions regarding the NEAT algorithm [closed]

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 ...
5
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1answer
829 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
239 views

How to create and train (with mutation and selection) a neural network to predict the next state of a board?

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. Technically, I have three questions, but I felt that they needed to ...
5
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1answer
539 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 ...
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1answer
212 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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536 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 ...
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1answer
544 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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3answers
167 views

Do genetic algorithms and neural networks really think?

I'm aware of those AI systems that can play games and neural networks that can identify pictures. But are they really thinking? Do they think like humans? Do they have consciousness? Or are they just ...
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2answers
455 views

What's the difference between biological and artificial evolution?

I am trying to understand the difference between biological and artificial evolution. If we look at it in terms of genetics, in both of them, the selection operation is a key term. What's the ...
4
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1answer
33 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 ...
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2answers
130 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?
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1answer
76 views

Can we use the Tierra approach to optimize machine code?

Thomas Ray's Tierra is a computer program which simulates life. In the linked paper, he argues how this simulation may have real-world applications, showing how his digital organisms (computer ...
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2answers
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When should I use simulated annealing as opposed to a genetic algorithm?

What kind of problems is simulated annealing better suited for compared to genetic algorithms? From my experience, genetic algorithms seem to perform better than simulated annealing for most problems....
4
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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 ...
4
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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
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1answer
323 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 ...
4
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1answer
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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 ...
4
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1answer
764 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 ...
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101 views

Why do we apply the mutation operation after generating the offspring?

Why do we apply the mutation operation after generating the offspring, in genetic algorithms?
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Can we use genetic algorithms to evolve datasets?

Genetic algorithms are used to solve many optimization tasks. If I have a dataset, can I evolve it with a genetic algorithm to create an evolved version of the same dataset? We could consider each ...
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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 ...