Introduction to Artificial Intelligence
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Artificial Intelligence is, in our
opinion, the most exciting area of computer science. Artificial
Intelligence (or AI, for short) is the name given to any attempt
to have computers gain attributes of the human mind.
Of course, this is a very vague statement, and much argument
has happened over what exactly constitutes AI (mathematicians and
scientists hate vague statements). There are essentially two schools
of thought: Strong AI and Weak AI.
Weak AI philosophers believe that computers, as advanced
as they may get, will only be able to seem intelligent. The
responses of the computer may seem like intelligent actions, but
the Weak AI theory insists that the computers are just mindlessly
manipulating data to produce "intelligent" actions. Strong AI philosophers believe that computers someday can
be as intelligent as humans.
Of course, the heart of the discussion is this: What
is intelligence? Normally, we declare that humans are
the standard for intelligence, but then, isn't human intelligence,
at the very basic level, just a bunch of mindless chemical reactions?
Both the Weak AI and the Strong AI have strong supporters, many
of them quite fanatic.
Aside from the philosophy of the Strong AI and the Weak AI debate,
there is also another, related, division in AI: Connectionism
Classicalism is the AI that is found in Chess programs,
weather diagnostics, and language processors. Classicalism, also
known as the top-down approach, approaches AI from the standpoint
that human minds are computational by nature, that is, we
manipulate data one piece at a time (serially) through a built in
circuitry in our brains. So, much of the classical approach to AI
consists of things like minimax trees, preprogrammed databases,
and prewritten code. Expert systems are another name for
Connectionism is the newer form of AI. The problem with
classicalism, connectionists say, is that it is too unlike the human
mind. The human mind can learn, expand, and change, but many
of the Expert systems are too rigid and don't learn. Connectionism
is the AI that the media really likes, which is why it contains
many famous names like Neural Networks and Parallel Processing.
Connectionism seems a step closer to the human mind, since it uses
networks of nodes that seem like the human brain's network of neurons.
Connectionism, however, also has its flaws. Connectionism is many
times inaccurate and slow, and currently connectionism has failed
to reach higher level AI, such as language and some advanced logic,
which humans seem to pick up easily in little time. Human intelligence
isn't built from scratch, like the Connectionist systems often
are. So, for those higher-level AI, Classicalism is by far the better
suited. Connectionism, however, is quite successful at modeling
lower level thinking like motor skills, face-recognition, and some
In the end, both viewpoints are valid in both debates. Regardless
of the viewpoint, however, the most important goal for AI
is that it helps us understand the mechanisms of the human mind.