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Issue #23
October 2004
By Dennis Merritt
AI - The art and science of making computers do interesting things
that are not in their nature.
Procedural Languages and AI
In this newsletter we've looked at symbolic languages like Mozart, SML,
Lisp and Prolog for developing AI applications. These languages are good
for AI because they make it easier to model and manipulate the knowledge
structures of a particular application domain. They allow the AI developer
to more readily create working prototypes and evolve those prototypes
as experience with an application grows.
If AI is the art and science of making computers do interesting things
not in their nature, then these languages are good for AI because
they all, to one degree or another, hide programming tasks related to
a computer's nature such as data typing, memory managment and defining
procedural code execution.
But they have the disadvantage of, well, not being standard procedural
programming languages. There is a lot to be said for being able to develop
AI applications in more mainstream languages. The disadvantage is, those
languages, while being well-suited to many conventional application areas,
are not particularly well-suited to implementing knowledge modelling,
reasoning algorithms, and other sorts of AI tools.<>
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