Questions tagged [genetic-algorithms]
A genetic algorithm is a class of adaptive stochastic optimization algorithms involving search and optimization. Genetic algorithms were first used by Holland (1975).
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Use PGO (profile guided optimization) to determine optimal value of variables in code
Reading this interesting paper it seems that a lot of performance loss is due to scheduling overhead in tight loops. To recap: There's a variable called "Chunksize" which determines how big ...
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Mentorship schedule matchmaking algorithm
A while ago, I tried to help a fella to develop a mentorship matchmaking program given the answers of a questionnaire to match mentors and mentees according to their respective skills and available ...
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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 move on a not-so-stupid level. First let me describe the grading function of the Alpha-Beta algorithm.
When it receives a ...
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Spreading objects in bags and bags' compartments
We have 10 bags. Each bag has 5 compartments numbered from 1 to 5. We have 100 objects to fill all the compartments and bags.
Compartment number x in a bag is identical to compartment of the same ...
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Why do we use binary encoding when it seems so inefficient?
When encoding our chromosome's characteristics (for want of a better word), binary seems to be the favoured method. I understand that this gives the maximum possibilities for crossover and mutation, ...
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How do you encode the genes when you don't know the length?
I think I've got the hang of writing a GA when you know the number of genes in a chromosome. For example, if you're searching for a string, and you know the length, you can just generate your initial ...
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Why have a crossover value that isn't 0.5?
Most of the literature I've read about GAs suggests using a crossover value of around 0.7, so you take the first 70% of one chromosome's genes, and the last 30% of the other to produce one new ...
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How do we know that the next generation will be better?
I was introduced to genetic algorithms recently by this MSDN article, in which he calls them combinatorial evolution, but it seems to be the same thing, and am struggling to understand how combining ...
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Perform crossover operation on AST in genetic programming
So in general when you perform a crossover in GA, you directly flip a random section in the "genome", with the corresponding section in the other parent, and mutate it based on the mutation rate.
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Is the output of a neural net supposed to have had the activation function applied to it?
TL; DR:
Is the output from a feed-forward neural a direct result of the activation function?
I.e: If the activation function is the sigmoid function, will the output always be between 0 and 1?
I'm ...
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PSO – how Dimensions are set up?
I am coding a Particle Swarm Optimization in C++. I have been for days trying to understand the theory of how dimensions work in each different problem.
In the many examples I have seen, all of them ...
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Shortest path to visit all nodes [duplicate]
I am given a set of tourist attractions(nodes identified by x, y) and i need to find the shortest path to visit them.
The way i thought of it, is i will ignore if there are streets available and ...
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What Algorithm can be use for task allocation based on location?
What algorithm can be use for task scheduling based on location? For example there are 100 students and 5 lecturers available.
Each lecturer must get same amount of student using location allocation ...
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Genetic Algorithm new generation exponentially increasing
I'm programming Genetic Algorithm in C++ and after searching all kind of ways of doing GA'a operators (selection, crossover, mutation) I came up with a doubt.
Let's say I have an initial population ...
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Is a genetic algorithm needed when computation is infinitely fast?
From what I understand, genetic algorithms try out multiple variations and evaluate the fitness of each variation. Then they select the best variations, change them a bit and continue the process with ...
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deciphering columnar transposition cipher
I am looking for an idea on how to decipher a columnar transposition cipher without knowing the key or the length of the key.
When I take the cipher text as input to my algorithm I will guess the ...
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Is it necessary to map integers to bits in a genetic algorithm?
From what I've read, genetic algorithms are usually (always?) applied to chromosomes of bits. So if a problem involves maximizing a function that takes integer values, the integers are first encoded ...
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using ant colony algorithm to create cross word game [closed]
I have difficulty to learn about ant colony algorithm (ACO), I have read about generating crossword game using (genetic algorithm) GA.I Know both of GA ant ACO usually used for optimization, but my ...
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MATLAB: Best fitness vs mean fitness, initial range
Based on the example of Rastrigin's function. At the plot function, if I chose 'best fitness', on the same graph 'mean fitness' will also be plotted. I understand well about 'best fitness' whereby it ...
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How close have we gotten to automating code writing? [closed]
And I don't mean Autocomplete or automatic code snippets as inserted by modern day editors, or polymorphic code. But what is the state-of-the-art in programs that can go through given inputs and types ...
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What's the best way to learn nature-inspired algorithms? [closed]
I completed the Machine Learning course (Stanford) and got very interested, also after some research, I decided that I'd like to learn nature-inspired algorithms.
I've found some resources like:
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Does defining the stopping point of a genetic algorithm defeat the purpose of the algorithm?
Wikipedia defines the termination point of a GA to this:
Commonly, the algorithm terminates when either a maximum number of
generations has been produced, or a satisfactory fitness level has
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Is a genetic algorithm a correct approach to this problem?
I am trying to calculate a set of items that produce the highest damage output in a video game. There are about 50 different items, of which you can choose 6. There are all sorts of conditions that ...
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