<artificial intelligence> (AI) The subfield of computer
science concerned with the concepts and methods of symbolic
inference by computer and symbolic knowledge representation
for use in making inferences. AI can be seen as an attempt to
model aspects of human thought on computers. It is also
sometimes defined as trying to solve by computer any problem
that a human can solve faster. The term was coined by
Stanford Professor John McCarthy, a leading AI researcher.
Examples of AI problems are computer vision (building a
system that can understand images as well as a human) and
natural language processing (building a system that can
understand and speak a human language as well as a human).
These may appear to be modular, but all attempts so far (1993)
to solve them have foundered on the amount of context
information and "intelligence" they seem to require.
The term is often used as a selling point, e.g. to describe
programming that drives the behaviour of computer characters
in a game. This is often no more intelligent than "Kill any
humans you see; keep walking; avoid solid objects; duck if a
human with a gun can see you".
See also AI-complete, neats vs. scruffies, neural
network, genetic programming, fuzzy computing,
artificial life.
ACM SIGART. U Cal Davis. CMU Artificial
Intelligence Repository.
