On 1/19/07, YKY (Yan King Yin) <[EMAIL PROTECTED]> wrote:

The bottomline is that the knowledge acquisition project is *separable* from
specific inference methods.

What is your argument supporting this strong claim?

I guess every book on knowledge representation includes a statement
saying that whether a knowledge representation format is good, to a
large extent depends on the type of inference it can support. These
two aspects are never considered as separable.

For example, First-Order Predicate Logic is not good enough for AI,
partly because it does not support non-deductive inference. Also,
semantic network is considered as "weak" mainly because it has no
powerful inference method associated.

You cannot build a useful knowledge base without thinking about what
inference methods it should support.

Pei

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