Why artificial intelligence people didn't use propositional natural programming language to represent knowledge?and is there's a relation between propositional logic and first order or predicate calculus?and if not what language the artificial intelligence people use in order to represent knowledge?
closed as not constructive by Hagen von Eitzen, rschwieb, Thomas, Norbert, J. M. Oct 21 '12 at 6:09
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Because, in a way, propositional logic only represents facts about finitely many objects, not knowledge. In other words, it doesn't allow you to deduce facts about objects you haven't seen before. If you want to represent knowledge, you'll want to be able to represent information such as: Objects always either have property $A$ or $B$, i.e. a sentence such as $$ \forall x\: (A(x) \lor B(x)) $$
In propositional logic, the best you can do is add all statements of the form $$ A_x \lor B_x $$ for all known objects $x$. But that doesn't allow you to deduce anything about a previously unknown $x$.
There doesn't exist any uncertainty in classical propositional logic. There also doesn't exist any room for error. When you look at real-world intelligence you can find both uncertainty and room for error in many places. If you know that a person stands 6 feet high, and you assume the background of classical propositional logic, that such a person stands at 6 feet tall, ends up as false. To say that a person stands 6 feet high means that they stand 6.000000... feet high, which almost surely almost never, if ever, holds in reality. So, it comes as a false statement and thus classical propositional logic always ends up failing to represent knowledge.
Artifical intelligence use a bunch of different techniques. The wikipedia probably will help you.