Genetic algorithms:
A) represent knowledge as groups of characteristics.
B) are software programs that work in the background to carry out specific, repetitive tasks.
C) develop solutions to particular problems using techniques such as mutation, crossover, and selection.
D) "learn" patterns from large quantities of data by sifting through data.
E) have a large number of sensing and processing nodes that continuously interact with each other.

Question

Quizplus · Accepted Answer

Genetic algorithms are a type of computational approach for solving problems which involve the evolution of possible solutions through techniques such as mutation, crossover, and selection. These algorithms mimic the process of natural selection to generate a population of potential solutions, which then "evolve" towards improving their fitness to the problem at hand. Thus, Option C accurately reflects the underlying methodology of genetic algorithms. Option A is more characteristic of expert systems, while Option B is related to background processes or daemons. Option D is similar to machine learning, and Option E is more related to neural networks or distributed computing.

Genetic Algorithms