Although knowledge representation is one of the
central and, in some ways, most familiar concepts in AI, the most fundamental question about
it—What is it?—has rarely been answered directly. Numerous papers have lobbied for one or
another variety of representation, other papers
have argued for various properties a representation should have, and still others have focused
on properties that are important to the notion of
representation in general.
In this article, we go back to basics to address
the question directly. We believe that the answer
what is a knowledge representation?
We argue that the notion can best
be understood in terms of five distinct roles that it plays, each crucial to the
task at hand:
First, a knowledge representation is most
fundamentally a surrogate, a substitute for the
thing itself, that is used to enable an entity to
determine consequences by thinking rather
than acting, that is, by reasoning about the
world rather than taking action in it.
Second, it is a set of ontological commitments, that is, an answer to the question, In
what terms should I think about the world?
Third, it is a fragmentary theory of intelligent reasoning expressed in terms of three
components: (1) the representation’s fundamental conception of intelligent reasoning,
(2) the set of inferences that the representation sanctions, and (3) the set of inferences
that it recommends.
Fourth, it is a medium for pragmatically
efficient computation, that is, the computational environment in which thinking is
accomplished. One contribution to this pragmatic efficiency is supplied by the guidance
that a representation provides for organizing
information to facilitate making the recommended inferences.
Fifth, it is a medium of human expression,
that is, a language in which we say things
about the world.
Understanding the roles and acknowledging their diversity has several useful consequences. First, each role requires something
slightly different from a representation; each
accordingly leads to an interesting and different set of properties that we want a representation to have.
Second, we believe the roles provide a
framework that is useful for characterizing a
wide variety of representations. We suggest
that the fundamental mind set of a representation can be captured by understanding how
it views each of the roles and that doing so
reveals essential similarities and differences.
Third, we believe that some previous disagreements about representation are usefully
disentangled when all five roles are given
appropriate consideration. We demonstrate
the clarification by revisiting and dissecting
the early arguments concerning frames and
logic.
Finally, we believe that viewing representations in this way has consequences for both
research and practice. For research, this view
provides one direct answer to a question of
fundamental significance in the field. It also
suggests adopting a broad perspective on
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