Questions tagged [evolutionary-algorithms]

For questions about evolutionary algorithms (EAs): a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. (Wikipedia)

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216 views

Can Metropolis be considered as evolutionary algorithm?

If we compare simple 1+1 evolutionary algorithm (e.g. Droste, Jansen, and Wegener, 2002) 1+1 evolutionary algorithm Set $p_m := 1/n$. Choose randomly an initial bit string $x \in \{0,1\}^...
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936 views

Forecasting Using Genetic Algorithms

I have come across some papers discussing the use of genetic algorithms as a forecasting tool. I don't however understand how a genetic algorithm, which to my (limited) knowledge is used to solve ...
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Measuring solution quality and allele impact on population fitness for a genetic algorithm

Situation: Let's say you're running a genetic algorithm to improve the way people are interacting with an online service. The alleles in each individual determine the exact behaviour of the service, ...
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1answer
216 views

How is the equation in “Evolution Strategies as a Scalable Alternative to Reinforcement Learning” derived?

In the OpenAI paper "Evolution Strategies as a Scalable Alternative to Reinforcement Learning", how is the equation in page 3 derived? Thanks.
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0answers
27 views

What is rotationally invariant crossover in Evolutionary optimization algorithms?

This article "Enhancing Differential Evolution Utilizing Eigenvector-Based Crossover Operator" design a rotationally invariant crossover, what is, in simple words, rotationally invariant crossover in ...
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1answer
29 views

Is Crossover only connected to Genetic algorithm?

Is the idea of crossover only restricted to Genetic Algorithms ? Are there any other evolutionary algorithms that uses crossover(even under another name ) ? If an algorithm uses crossover but does ...
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1answer
581 views

How do I design this multi-objective fitness function for use with genetic algorithm?

I have a multi-objective optimization problem that I am applying genetic algorithm (GA) to solve. Currently, there are only 2 objectives: minimize cost maximize validity The cost minimization is ...
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1answer
56 views

What is the difference between the study of Evolutionary algorithm vs. Optimization?

I have a course named "Evolutionary Algorithm". But, our teacher is always mentioning the word "Optimization" in his lectures. I am confused. Is he actually teaching Optimization? If yes, why is the ...
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1answer
64 views

Which statistical test would be most appropriate for this data?

I conducted an experiment in an evolutionary program called AVIDA-ED contrasting the adaptive evolution in different world sizes (30x30,40x40,50x50). I performed 10 repetitions of each world size and ...
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0answers
10 views

How to minimise a quantity using a Genetic Algorithm

I'm somewhat new to Genetic Algorithms and I've been exploring the use of them to minimize a quantity (Y), where my optimum value is a small negative value. I've implemented an algorithm that has a ...
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1answer
38 views

How to tune hyperparameters/architecture of networks that are expensive to train?

What are some recommended ways to tune hyperparameters and/or develop domain-specific architectures for a large neural network model? That is, how to further tune a large neural network that already ...
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1answer
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How to derive the gradient of the reparameterized score function estimator?

In the paper Evolution Strategies as a Scalable Alternative to Reinforcement Learning, the authors derive the following gradient of the score function estimator $$ \begin{align} \nabla_\psi\mathbb E_{...
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1answer
63 views

Sensitivity of Evolutionary algorithms to underlying random number generators

Techniques of evolutionary algorithms (EA) rely heavily on the use of random number generators (RNGs). From initial population generation, through the specific canonical operators applied to create ...
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1answer
24 views

What is the reason behind the weight updates in Evolution Strategies?

OpenAI introduced Evolution Strategies as an alternative to reinforcement learning technique without backpropagation. A sample code from their website, ...
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1answer
27 views

Evolution strategies global recombination question

In evolution strategies the genotype has object variables and strategy variables as alleles (and sometimes the alpha values). I'm reading the book Introduction to Evolutionary Computing (A.E. Eiben, ...
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1answer
162 views

Crossover and mutation with constraints

I had some experience with genetic algorithms during my computer science studies. I wanted to refresh my knowledge and decided to write a simple prototype for automated seating people at tables (e.g. ...
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What is the best approach to training AI to play snake using NEAT? [closed]

If this is not the right place to ask this question then please refer me to the correct place where I can ask it. I created a snake game using pygame and I am trying to teach an AI to play the game ...
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What is the most efficient algorithm for hyper-parameter optimization, specially when comparing Bayesian optimisation and evolutionary algorithms?

I've been reading some papers about how Bayesian optimisation has achieved great results in hyper-parameter tuning when compared with random search or grid search. What about when comparing with ...
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62 views

Unexpected fitness values: Neat-Python

I am currently working on implementing the Neat-Python library to run some neural networks. The below code works and I have also included the configuration file I have used. The problem in question ...
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0answers
15 views

Conducting Statistical Analysis on Evolving Populations

I am writing a paper on the evolution of altruism. To do so, I have written a computer program that simulates the environment and allows a population to evolve. Organisms are either altruists or are ...
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29 views

How to compare the performance of Evolutionary Algorithms

I need to compare the performance of 3 Evolutionary algorithms on some Benchmark functions. Evolutionary algorithms are a heuristic-based approach which are used to solve optimization problems. I ...
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126 views

Sample a probability distribution with an evolutionary algorithm?

I've been doing some initial level reading on Markov chain Monte Carlo (MCMC). For what I can tell given a probability distribution $P(x_1, x_2, ..., x_N)$ (dependent on $N$ parameters), MCMC ...