Genetic Algorithms: Concepts and Features
5 Questions
0 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

What is a genetic algorithm used for?

  • Finding a good solution to a problem (correct)
  • Analyzing data
  • Calculating statistics
  • Making predictions
  • What type of selection mechanism is sensitive for converging populations with close fitness values?

  • Roulette Selection
  • Rank Selection
  • Tournament Selection (correct)
  • Fitness Proportionate Selection
  • What is the purpose of Order-1 crossover?

  • Exploitation
  • Exploration (correct)
  • Mutation
  • Steady-state replacement
  • What is elitism used for?

    <p>Keeping the best solutions discovered so far</p> Signup and view all the answers

    What is schema theory used for?

    <p>Explaining the efficacy of genetic algorithms</p> Signup and view all the answers

    Study Notes

    • A genetic algorithm (GA) is a computer program that tries to find a good solution to a problem by evolving a population of candidate solutions.
    • The GA maintains a population of solutions and makes it evolve by iteratively applying a set of stochastic operators.
    • The GA has been subject of many (early) studies and still often used as a benchmark for novel GAs.
    • The GA shows many shortcomings, e.g. it is too restrictive in its representation of solutions, mutation and crossovers only applicable for bit-string and integer representations, and selection mechanism sensitive for converging populations with close fitness values.
    • We will use Tournament Selection to choose a solution and place it in the mating pool. Two other solutions will be picked and another solution in the mating pool will be filled up with the better solution.
    • Order-1 crossover is explorative and mutation is exploitative.
    • Mating individualsto generate pop_size offspring is a steady-state replacement process.
    • Each individualsurvives for exactly one generation and the entire set of parents is replaced by the offspring.
    • The elitism option is used to keep one or more of the best solutions discovered so far and copy them to the next generation.
    • Schema theory seeks to give a theoretical justification for the efficacy of the field of genetic algorithms.
    • What is a schema:
    • a template for new gene arrangements  {0,1,*} where * is a don't care.
    • Schema is favorable traits in a solution, where a favorable schema is called an above average schema.

    Studying That Suits You

    Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

    Quiz Team

    Description

    Explore the concepts and features of genetic algorithms through this quiz. Learn about population evolution, stochastic operators, shortcomings, selection mechanisms, crossover and mutation techniques, and the application of schema theory. Test your knowledge about genetic algorithms and their use as a benchmark for novel GAs.

    More Like This

    Use Quizgecko on...
    Browser
    Browser