edith@ai.toronto.edu (Edith Fraser) (03/01/90)
Department of Computer Science, University of Toronto
(GB = Galbraith Building, 35 St. George Street)
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ARTIFICIAL INTELLIGENCE
GB305, at 11:00 a.m., 15 March 1990
Scott Goodwin
University of Alberta
"Statistically Motivated Defaults"
A fundamental area of research in Artificial Intelligence is the
development of a computational theory of common sense reasoning. My work,
as well as the work of several other researchers, has shown that the
foundations of such a theory can be laid by viewing common sense reasoning
as a rudimentary kind of scientific reasoning. This view is solidly rooted
in the philosophy of science.
My colleagues and I have proposed a simple hypothetical reasoning
framework, called THEORIST. We have shown the conceptual efficiency of this
framework and its applicability to a wide range of common sense reasoning
tasks such as reasoning by analogy, planning, diagnosis, and image
understanding.
My work focused on one aspect of THEORIST, viz., the semantics of defaults.
In common sense reasoning, some knowledge is generally true but admits
exceptions (e.g., birds fly, objects retain their colour when moved, and
people with colds cough). Knowledge of this type is referred to as
defaults. I view a default as a possible hypothesis that can be assumed in
some cases. Further, I view a default as making a statistical claim about
the world. It is the statistical knowledge encoded by the default that
justifies assuming it in particular cases. In general, we may know many
things about particular cases but not all of this knowledge is relevant to
the applicability of defaults. In probability theory, the problem of
identifying the relevant knowledge is called the problem of choosing the
reference class. One contribution of my work is in addressing this problem.
Additional problems arise in reasoning about time. In particular, there is
the problem of persistence: how to formalize the common sense knowledge
that most things remain the same from one moment to the next. Much
attention has been focused on this problem and many technical solutions
have been proposed. Yet little is understood about this problem at a
fundamental level. This talk identifies three important problems that arise
in temporal reasoning and discusses their solution in light of the proposed
interpretation of defaults.