Evolutionary Algorithms in Computational Intelligence Quiz
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Questions and Answers

Which of the following is true about evolutionary algorithms?

  • They are a subset of evolutionary computation. (correct)
  • They are a subset of computational intelligence.
  • They are a type of machine learning algorithm.
  • They are a type of genetic algorithm.

What mechanisms are used by evolutionary algorithms?

  • Sampling, clustering, classification, and regression.
  • Sorting, searching, merging, and indexing.
  • Reproduction, mutation, recombination, and selection. (correct)
  • Addition, subtraction, multiplication, and division.

What role do candidate solutions play in evolutionary algorithms?

  • They play the role of optimization problems.
  • They play the role of fitness functions.
  • They play the role of evolutionary operators.
  • They play the role of individuals in a population. (correct)

Why do evolutionary algorithms often perform well in approximating solutions?

<p>They do not make any assumption about the underlying fitness landscape. (D)</p> Signup and view all the answers

What are the limitations of techniques from evolutionary algorithms applied to the modeling of biological evolution?

<p>They are generally limited to explorations of microevolutionary processes and planning models based upon cellular processes. (C)</p> Signup and view all the answers

Flashcards

Evolutionary Algorithms

A subset of evolutionary computation using reproduction, mutation, recombination, and selection to find solutions.

Candidate Solutions

Solutions in the population of evolutionary algorithms, representing individuals.

Reproduction

A mechanism in evolutionary algorithms that creates new solutions from existing ones.

Mutation

A mechanism in evolutionary algorithms that introduces small random changes to solutions.

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Recombination

A mechanism in evolutionary algorithms blending parts of different solutions to create new ones.

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Selection

A mechanism in evolutionary algorithms selecting the best solutions for reproduction.

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Fitness Landscape

The relationship between different solutions and their fitness values.

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Microevolutionary

Evolutionary processes over relatively short periods.

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Evolutionary Algorithms Limitations

Limited to approximating solutions without assumptions about the fitness landscape, but often limited to microevolution.

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Cellular Processes

Biological processes occurring within cells.

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