Nicholas Cassimatis, Asst. Prof, CogSci

 

Nicholas Cassimatis, Asst. Prof, CogSci

Sage 4101

September 9, 2009 12:00 PM - 1:30 PM

Abstract: Systems with human-level intelligence must both be flexible and be able to reasonin an appropriate time scale. These two goals are in tension, as manifest by the contrastingproperties of structured knowledge-based systems (e.g., involving scripts and frames) and general inference algorithms.  The problem of resolving ambiguous, implicit and non-literal references exemplifies many of these difficulties. We describe an approach, called reasoned unification, for dealing with these challenges by representing and jointly reasoning over linguistic and non-linguistic knowledge (including structures such as scripts and frames) within the same inference framework.  Reasoned unification enables a treatment of several reference resolution phenomena that to our knowledge have not previously been the subject of a unified analysis. This analysis illustrates how reasoned unification can resolve many difficult problems with using complex knowledge structures while maintaining their benefits. 

Resolving Ambiguous, Implicit and Non-Literal References....

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