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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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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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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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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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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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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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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553 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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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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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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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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208 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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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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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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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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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 ...
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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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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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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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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 ...