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.