AI Meets Decision Science: Emerging Synergies For Decision Support

  • Edward H. Shortliffe
Conference paper
Part of the NATO ASI Series book series (volume 97)


In the 1970s, the field of medicine forced clinically-oriented AI researchers to develop ways to manage explicit statements of uncertainty in expert systems. Classical probability theory was considered, discussed, and even tried, but it tended to be abandoned because of four major limitations that were encountered in efforts to apply it formally:
  1. 1.

    Limitations due to the perceived need to assume conditional independence;

  2. 2.

    Major difficulties with the collection or assessment of conditional probabilities for use in these data-hungry approaches;

  3. 3.

    Cognitive complexity in dealing with large tables of conditional probabilities and their interrelationships;

  4. 4.

    Computational complexity that resulted if rigorous probabilistic approaches were attempted.



Expert System Decision Theory Conditional Independence Similarity Network Advisory Tool 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Edward H. Shortliffe
    • 1
  1. 1.Section on Medical InformaticsStanford University School of MedicineStanfordUSA

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