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ARTIFICIAL CREATIVITY
The development of informational technology
gives a lot of new possibilities to use computer
in other non standard fields of using. I have in
mention a lot of researches where computer
simulates human thinking, creating new solutions
and resolving different problems in a way of
intelligence data processing. Artificial
creativity is a growing area of artificial
intelligence, which draws from and adds to
diverse areas such as visual art, music,
mathematics, science, literature and humour, as
well as traditional areas such as cognitive
science and computer science.
There are many definitions of human creativity but
one of them include the ability to take existing
objects and combine them in different ways for
new proposes, wit other words the creativity is
the action of combining previously not combined
structures or objects. Creativity is the ability
to create novel and useful ideas and solutions
to everyday problems and challenges. Creativity
is also the origination of new ideas that were
previously non-existent. Often great solutions
are products of silly ideas. Silly ideas are
those that do not seem to follow rules, and are
consequently thrown out, but modification of
these ideas can result in a different path to
the desired objective through unusual
connections.
And now a short analysis of what, in the most
general terms, artificial creativity (AC) is. AC
is a field that tries to determine in
computational details how creativity works. But
for AC to play this role we need to be able to
understand creativity of different non-human
kinds and believe that this is something that
human-designed machines can achieve. If we can
now construct successful models that accord with
general account of creativity, then we can and
should think of them as creative systems. Now is
opening a very important question: how to make a
computer creative if we know that computers can
only blindly follow fixed rules defined in the
program. We find the answer of this question in
the special types of programmes called genetic
algorithm. The genetic algorithm is a model of
machine learning, which derives its behaviour
from a metaphor of processes of evolution in
nature. This is done by the creation within a
machine of population of individual programs and
then they go through a process of evolution
using reproduction, selection, mutation and
crossover operations producing new solutions.
Let see other explanation of AC from the point of
view of a computer program. Creativity of a
computer program is how good it is at finding
unexpected solutions to problems. There are two
very important key words here: solutions and
unexpected. It is important that the creative
solutions actually solve something otherwise the
most creative entity in the universe would be a
random number generator. Unexpected solutions
are fundamental for any kind of creativity. If
the author of the program, or another person who
understands how the program works can be
surprised on generated solutions it means that
they find it creative. In a program that isn’t
creative, the programmer can understand exactly
how the program arrived to a particular solution.
A creative program arrives to solutions, that
are both unexpected by people and the author can’t
understand the exact of way of how the program
managed to obtain the solution. Although the
programmer understands the principle of how the
program works, he can’t mentally retrace the
route taken by the program to arrive to a
particular solution.
Different experts from the area of computer
programming don’t consider unpredictability as
the possible solution of the program.
Unpredictable solution could be caused only by
the program or data error. All programs are
essentially algorithmic and a programmer can in
principle trace how a program has created
something which can demystify the process and
may detract form our judgement of its creativity.
My answer is very simple: let them try to do.
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