Another type of artificial intelligence technology involves genetic
algorithms. Genetic algorithms are part of the general class known as:

A.
Suboptimal computing

B.
Biological computing

C.
Evolutionary computing

D.
Neural networks

Explanation:
Evolutionary computing uses the Darwinian principles of survival of
the fittest, mutation, and the adaptation of successive generations of
populations to their environment. The genetic algorithm implements
this process through iteration of generations of a constant-size population
of items or individuals. Each individual is characterized by a
finite string of symbols called genomes. The genomes are used to represent
possible solutions to a problem in a fixed search space. For
example, if the fixed population of the first generation of individuals
consists of random binary numbers, and the problem is to find the
minimum binary number that can be represented by an individual,
each binary number is assigned a fitness value based on the individuals
binary number value. The smaller the binary number represented
by a parent individual, the higher level of fitness that is
assigned to it. Through cross breeding among the numbers (known
as crossover), mutations of the numbers, and pairing of numbers with
high fitness ratings, the smallest value that can be represented by the
number of bits in the binary number will emerge in later generations.
*Answer neural networks, is incorrect and has been discussed
extensively in previous questions in this chapter.
*Answer Suboptimal computing is a distracter and answer biological computing, refers to
computation performed by using certain characteristics of living organisms.