[mod.ai] Seminar - Belief Functions in Artificial Intelligence

holland@GMR.CSNET (Steve Holland) (03/04/86)

Seminar at General Motors Research Laboratories, Warren, Michigan:

      
                 Belief Functions in Artificial Intelligence
                             Prof. Glenn Shafer
                            University of Kansas
                           Lawrence, Kansas  66045
      
                           Thursday, March 6, 1986
      
                                  ABSTRACT
     The theory of belief functions, or the Dempster-Shafer theory, has
     attracted wide interest as a tool for the management of uncertainty in
     artificial intelligence.
      
     What are the advantages and disadvantages of belief functions when they are
     compared with numerical alternatives such as Bayesian probability and fuzzy
     logic or with non-numerical alternatives such as default logic and the
     calculus of endorsements?  What are the current prospects for sensible use
     of belief functions in expert systems?
      
     In this talk, I will offer some general judgments on these questions.  I
     will emphasize the need for interactive tools for the construction of
     probability arguments, and I will speculate on long-term possibilities for
     probability judgment using man-made associateve memories.
      

-Steve Holland, Computer Science Department