voula@utcsri.UUCP (Voula Vanneli) (04/10/85)
UNIVERSITY OF TORONTO
DEPARTMENT OF COMPUTER SCIENCE
(GB = Galbraith Bldg., 35 St. George St.)
ARTIFICIAL INTELLIGENCE SEMINAR - Wednesday, April 10, 4 pm,
GB 244
Jim Hendler
Dept. of Computer Science, Brown University
Studies of Market Passing in Knowledge Representation
and Problem Solving Systems.
Abstract
A standard problem in Artificial Intelligence systems that
do planning or problem solving is called the "late-
information, early-decision paradox." This occurs when the
planner makes a choice as to which action to consider, prior
to encountering information that could either identify an
optimal solution or that would present a contradiction. As
the decision is made in the absence of this information it
is often the wrong one, leading to much needless processing.
In this talk I describe how the technique known as "marker-
passing" can be used by a problem-solver. Marker-passing,
which has been shown in the past to be useful for such cog-
nitive tasks as story comprehension and word sense disambi-
guation, is a parallel, non-deductive, "spreading activa-
tion" algorithm. By combining this technique with a plan-
ning system the paradox described above can often be circum-
vented. The marker-passer can also be used by the problem-
solver during "meta-rule" invocation and for finding certain
inherent problems in plans. An implementation of such a
system is discussed as are the design "desiderata" for a
marker-passer.