[comp.ai.digest] Seminar - Solving Dynamic-Input Interpretation Problems

finin@PRC.UNISYS.COM (Tim Finin) (01/19/88)

				     
				AI Seminar
			 UNISYS Knowledge Systems
			   Paoli Research Center
				 Paoli PA


	    SOLVING DYNAMIC-INPUT INTERPRETATION PROBLEMS
				   
			 Kathleen D. Cebulka
		  Computer and Information Sciences
			University of Delaware
			   Newark, DE 19716
				   
Many AI problems can be viewed as interpretation problems which have the
common goal of producing a solution that "explains" a given input.  The
solution usually takes the form of a set of beliefs called a hypothesis.
Although a number of researchers have developed strategies for handling the
static case where the input is fixed, there are many problems where the
input is received dynamically in relatively small increments.  Usually the
problem solver is interacting with a user who expects a timely response
after every input, so it can not postpone forming a solution while it waits
for more complete information.  As a result, the problem solver must rely
on default reasoning and belief revision techniques since new evidence may
reveal that the current hypothesis is not the final answer.

This talk describes a characterization of the solution of dynamic-input
interpretation problems as a search through a hypothesis space.  A domain
independent algorithm, called the Hypothesize-Test-Revise algorithm, is
presented and contrasted with the traditional static approach.  An
advantage of this algorithm is a more efficient strategy for generating and
revising hypotheses in a dynamic environment.
				     
		       2:00pm Wednesday, January 20
			    BIC Conference Room
		       Unisys Paloi Research Center
			Route 252 and Central Ave.
			      Paoli PA 19311
				     
     -- non-Unisys visitors who are interested in attending should --
     --   send email to finin@prc.unisys.com or call 215-648-7446  --