5 Questions
What is the primary purpose of a genetic algorithm?
To find a good solution to a problem
What is the main difference between mutation and crossover?
Mutation is exploitative and crossover is explorative
What is the process called when a set of parents is replaced by the offspring?
Steady-state replacement
What is the main goal of schema theory?
To give a theoretical justification for the efficacy of genetic algorithms
What is a schema?
A template for new gene arrangements
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.
Test your knowledge about genetic algorithms, a computer program for finding solutions through evolving populations of candidate solutions. This quiz covers topics such as genetic algorithm operators, shortcomings, selection mechanisms, and schema theory.
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