Answers.Body: <p>Dempster-Shafer Theory was studied fairly seriously in AI through the 70's and 80's. However, Dempster-Shafer theory has some serious shortcomings, that will cause an agent that uses it to make irrational decisions. These were uncovered by Pearl and others in the 80's, with more problems emerging in later years.</p>
  
  <p>See <a href="https://www.ijcai.org/Proceedings/85-2/Papers/064.pdf" rel="nofollow noreferrer">Cheeseman</a> for a summary of the arguments that probability is the only suitable framework for reasoning under-uncertainty in AI (which is the current orthodox view), along with <a href="https://ieeexplore.ieee.org/document/6289948" rel="nofollow noreferrer">Josang &amp; Harkin 2012</a> (which develops a theory that subsumes Dempster-Shafer, and under which DS can be shown to lead to poor decisions), and Pearls' <a href="https://www.sciencedirect.com/science/article/pii/0888613X8890117X?via%3Dihub" rel="nofollow noreferrer">On Probability Intervals</a>.</p>
  
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Answers.CreationDate: 2019-11-19T22:06:55.890Z
Answers.LastActivityDate: 2019-11-19T22:06:55.890Z
Answers.UserDisplayName: John Doucette
Body: <p>How does <a href="https://plato.stanford.edu/entries/formal-belief/#DemShaThe" rel="nofollow noreferrer">Dempster-Shafer theory</a> work in representing ignorance in the AI field?</p>
  
Tags: <dempster-shafer-theory>
Title: How Dempster-Shafer theory work in AI?
UserDisplayName: Marosh Fatima
ThreadText: # How Dempster-Shafer theory work in AI?
  
  (Asked by: username_0 on 2018-11-25)
  
  How does [Dempster-Shafer theory](https://plato.stanford.edu/entries/formal-belief/#DemShaThe) work in representing ignorance in the AI field?
  
  **Tags:** dempster-shafer-theory
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2019-11-19. Score: 1
  
  Dempster-Shafer Theory was studied fairly seriously in AI through the 70's and 80's. However, Dempster-Shafer theory has some serious shortcomings, that will cause an agent that uses it to make irrational decisions. These were uncovered by Pearl and others in the 80's, with more problems emerging in later years.
  
  See [Cheeseman](https://www.ijcai.org/Proceedings/85-2/Papers/064.pdf) for a summary of the arguments that probability is the only suitable framework for reasoning under-uncertainty in AI (which is the current orthodox view), along with [Josang & Harkin 2012](https://ieeexplore.ieee.org/document/6289948) (which develops a theory that subsumes Dempster-Shafer, and under which DS can be shown to lead to poor decisions), and Pearls' [On Probability Intervals](https://www.sciencedirect.com/science/article/pii/0888613X8890117X?via%3Dihub).
  
  
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