P. Haddawy, J. Jacobson, and Charles E. Kahn. Banter: A bayesian network tutoring shell. Artificial Intelligence in Medicine, 10(2):177--200, 1997.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....previously. As a consequence B andC facilitate the execution of E. Table1. P(D B,C) B F F T T D C F T F T F .5 .2 .3 .1 T .5 .8 .7 . 9 The usefulness of BNs has been shown in many real world applications, for example, the Microsoft s Office Assistant [17] the Bayesian Network Tutoring Shell [15] and the Lockheed Martin unmanned underwater vehicle [25] Despite these experiences, their usage in the field of MAS is still small. The next section describes an extension of Bayesian networks which in addition to representing uncertain knowledge, can use this knowledge to make decisions. 2.3 ....

P. Haddawy, J. Jacobson, and Charles E. Kahn. Banter: A bayesian network tutoring shell. Artificial Intelligence in Medicine, 10(2):177--200, 1997.

....are expressed numerically. There is no user model, and the only adaptation capability is that the user can control the level of detail in the selection of diagnoses by modifying the relevance and certainty thresholds. 3.3. 7 BANTER Based on Suermondt s method INSITE, Haddaway, Jacobson and Kahn [27, 28, 29] have developed BANTER, a tool for decision support and training, especially in medicine, although it works on any network consisting of hypotheses, observations and diagnostic procedures. Given a certain evidence, BANTER can o er the probability of a hypothesis or select the most informative test ....

P. Haddawy, J. Jacobson, and C. Kahn. BANTER: A Bayesian network tutoring shell. Artical Intelligence in Medicine, 10:177200, 1997.

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